Quick Verdict
Sellforte scores 39.5 out of 49 in our structured evaluation; Mutinex scores 25 out of 49.
Mutinex is a channel-level MMM platform with a strong conversational AI interface called MAITE. It covers marketing data reporting, historical performance insights, and channel-level spend optimization well. Its main limitations are the absence of campaign and ad set-level optimization, no incrementality testing capabilities, and an MMM that is not calibrated with incrementality tests.
Sellforte is the broader platform: it covers channel- and campaign-level optimization, all three incrementality test types (geo, A/B, and conversion lift), a fully integrated MMM, and meets enterprise IT requirements that Mutinex does not address.
If you are a large enterprise focused purely on channel-level spend optimization and do not need campaign-level execution or causal experimentation, Mutinex is a reasonable fit. If you need campaign and ad set-level optimization, incrementality testing, a calibrated MMM, or enterprise-grade IT compliance, Sellforte is the stronger choice.
Introduction and Table of Contents
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This article compares Mutinex and Sellforte head-to-head on conversational AI capabilities for MMM and incrementality testing, using the same 49-criterion framework we developed for our in-depth comparison of all major vendors in this category. Here's what we're covering in this article:
- Quick Verdict
- How We Evaluated
- About the Vendors
- Side-by-Side Scorecard
- Category-by-Category Breakdown
- Marketing Data Reporting via Conversational AI
- Historical Performance Insights and Causal Explanation via Conversational AI
- Channel-Level Optimization with Conversational AI
- Campaign and Ad Set-Level Optimization with Conversational AI
- Incrementality Testing with Conversational AI
- Agentic Execution and Autonomy
- AI UX and Conversational Interface
- Analytical Backbone
- Enterprise-Grade Platform
- Where Mutinex Wins
- Where Sellforte Wins
- Which Should You Choose?
- Frequently Asked Questions
How We Evaluated
Both platforms are scored against the same 49-criterion, 9-category framework developed for our in-depth comparison of AI tools for MMM and Incrementality Testing in 2026. The criteria and the methodology behind them are presented in full in How to Choose an AI Tool for MMM and Incrementality Testing: 49 Evaluation Criteria. They were derived from more than 1,660 real AI prompts and 700 discussions with marketers and marketing analytics professionals across retail, ecommerce, DTC, travel, and restaurants.
Each criterion is scored 1 (fully supported), 0.5 (partially supported or inconclusive evidence), or 0 (not supported or no public evidence found). Scores are based on public first-party vendor documentation, vendor-disclosed information on third-party platforms, and third-party review sites. Absence of evidence counted as 0.
About the Vendors
About Mutinex
Mutinex is a marketing measurement company focused on Marketing Mix Modeling, with a conversational AI interface called MAITE built on top of its GrowthOS MMM platform.
Mutinex is fundamentally a channel-level MMM platform that has added a conversational AI layer to make MMM insights more accessible to marketers. MAITE supports marketing data reporting, historical performance insights, and channel-level spend optimization through natural language. Mutinex does not offer a public demo without a sales call, which made this evaluation more dependent on published product documentation and marketing material than some other vendors.
About Sellforte
Sellforte is a SaaS platform that unifies Marketing Mix Modeling, Incrementality Testing, and Attribution into a single operating system for retail and ecommerce, with a conversational AI interface covering the full stack.
Unlike most other measurement vendors, Sellforte measures incremental ROAS at the campaign and ad set level, providing spend and bidding recommendations for tactical budget steering. Conversational AI is one major component of the Sellforte platform, alongside Marketing Mix Modeling, incrementality testing, and incrementality-corrected attribution. Sellforte is used by enterprise retailers and ecommerce brands including bonprix, Lidl, C&A, Douglas, and Tchibo. Sellforte's conversational AI can be evaluated through a public demo at demo.sellforte.com without a sales call.
Side-by-Side Scorecard
| Category | Mutinex | Sellforte |
|---|---|---|
| 1. Marketing Data Reporting via Conversational AI | 4 / 4 | 4 / 4 |
| 2. Historical Performance Insights and Causal Explanation via Conversational AI | 4 / 5 | 5 / 5 |
| 3. Channel-Level Optimization with Conversational AI | 5 / 5 | 4.5 / 5 |
| 4. Campaign and Ad Set-Level Optimization with Conversational AI | 0 / 6 | 4 / 6 |
| 5. Incrementality Testing with Conversational AI | 0 / 6 | 2.5 / 6 |
| 6. Agentic Execution and Autonomy | 1 / 4 | 2 / 4 |
| 7. AI UX and Conversational Interface | 5 / 8 | 6.5 / 8 |
| 8. Analytical Backbone | 2 / 4 | 4 / 4 |
| 9. Enterprise-Grade Platform | 4 / 7 | 7 / 7 |
| Total score out of 49 | 25 | 39.5 |
Category-by-Category Breakdown
1. Marketing Data Reporting via Conversational AI (Mutinex: 4/4, Sellforte: 4/4)
| Criterion | Mutinex | Sellforte |
|---|---|---|
| 1.1 AI reports sales progress for online sales | 1 | 1 |
| 1.2 AI reports sales progress for offline store sales | 1 | 1 |
| 1.3 AI reports digital media data (spend, impressions, clicks) | 1 | 1 |
| 1.4 AI reports offline media data | 1 | 1 |
| Category total | 4 / 4 | 4 / 4 |
Marketing data reporting is a tie. Both Mutinex and Sellforte score a perfect 4 out of 4 in this category. Both platforms surface online and offline sales data, digital media KPIs across major paid channels, and offline media spend and performance through their conversational AI interfaces. For teams whose primary need is a natural language interface to raw marketing data, both tools deliver equally at this foundational level.
2. Historical Performance Insights and Causal Explanation via Conversational AI (Mutinex: 4/5, Sellforte: 5/5)
| Criterion | Mutinex | Sellforte |
|---|---|---|
| 2.1 AI measures incremental ROAS and incremental revenue for each digital channel | 1 | 1 |
| 2.2 AI measures incremental ROAS and incremental revenue for each offline channel | 1 | 1 |
| 2.3 AI-reported incremental ROAS is updated daily | 0 | 1 |
| 2.4 AI reports promotion-driven revenue, in addition to media-driven | 1 | 1 |
| 2.5 AI explains why performance has changed (promotions, seasonality, weather, saturation) | 1 | 1 |
| Category total | 4 / 5 | 5 / 5 |
Mutinex performs strongly in this category, scoring 4 out of 5. Its AI reports incremental ROAS and incremental revenue for both digital and offline channels, surfaces promotion-driven revenue alongside media-driven revenue, and ties performance changes to causal drivers such as promotions, seasonality, and weather. This is a genuine strength relative to many other tools in this category.
The one gap is that Mutinex's incremental ROAS measurement is not updated daily. Sellforte scores a perfect 5 out of 5 by providing daily measurement of incremental ROAS across all channels. For advertisers who need to monitor performance shifts in near real time, this distinction matters: weekly or less frequent model updates mean that short-term media changes are not reflected until the next model run.
3. Channel-Level Optimization with Conversational AI (Mutinex: 5/5, Sellforte: 4.5/5)
| Criterion | Mutinex | Sellforte |
|---|---|---|
| 3.1 AI recommends optimal budget allocation by channel | 1 | 1 |
| 3.2 AI forecasts total revenue based on optimal budget allocation | 1 | 1 |
| 3.3 AI provides miROAS and response curves for each channel | 1 | 0.5 |
| 3.4 AI supports basic custom scenario planning (e.g., "what if I cut Meta by 20%?") | 1 | 1 |
| 3.5 AI supports advanced scenario planning in natural language (constraints, multi-dimensional optimization) | 1 | 1 |
| Category total | 5 / 5 | 4.5 / 5 |
This is the one category where Mutinex outscores Sellforte, earning a perfect 5 out of 5. Mutinex's background as an MMM platform is evident here: its AI recommends optimal budget allocation across channels, forecasts total revenue under the recommended allocation, provides marginal incremental ROAS and response curves per channel, and supports both basic and advanced scenario planning in natural language, including constraints and multi-dimensional optimization.
Sellforte scores 4.5 out of 5, with the small gap on miROAS and response curve presentation via the conversational AI interface specifically. Both platforms are strong choices for channel-level optimization, and for most buyers this single criterion difference will not be decisive.
4. Campaign and Ad Set-Level Optimization with Conversational AI (Mutinex: 0/6, Sellforte: 4/6)
| Criterion | Mutinex | Sellforte |
|---|---|---|
| 4.1 AI provides incremental ROAS of each campaign and ad set | 0 | 1 |
| 4.2 AI compares incremental ROAS to last-click and ad platform attribution ROAS | 0 | 1 |
| 4.3 AI provides miROAS for each campaign and ad set | 0 | 0.5 |
| 4.4 AI recommends optimal spend for each campaign and ad set | 0 | 0.5 |
| 4.5 AI recommends optimal bid value for each campaign and ad set | 0 | 0.5 |
| 4.6 AI provides pre/post analysis for each bidding change | 0 | 0.5 |
| Category total | 0 / 6 | 4 / 6 |
This is one of the sharpest gaps in the comparison. Mutinex scores 0 across all six criteria in this category. Its conversational AI operates at the channel level and does not surface incremental ROAS, miROAS, or spend and bid recommendations at the campaign or ad set level. There is no pre/post analysis for executed bidding changes. For advertisers who want to translate channel-level budget recommendations into actionable campaign-level execution, Mutinex does not provide a path within the platform.
Sellforte scores 4 out of 6. Its AI surfaces incremental ROAS for each campaign and ad set, compares it to last-click and platform-reported ROAS, and provides partial coverage of miROAS, spend recommendations, bid recommendations, and pre/post analysis at the campaign and ad set level. This makes Sellforte the stronger choice for advertisers who need incremental measurement and optimization at the campaign and ad set level.
The practical implication is significant. A budget shift from Meta to TikTok at the channel level is not actionable until it is translated into specific bid and spend changes across individual campaigns and ad sets. Mutinex leaves that translation step entirely outside the platform.
5. Incrementality Testing with Conversational AI (Mutinex: 0/6, Sellforte: 2.5/6)
| Criterion | Mutinex | Sellforte |
|---|---|---|
| 5.1 Summarizes all incrementality tests done by the company | 0 | 0.5 |
| 5.2 Provides in-depth report for geo tests | 0 | 0.5 |
| 5.3 Provides in-depth report for own media A/B tests | 0 | 0.5 |
| 5.4 Provides in-depth report for Conversion Lift tests | 0 | 0.5 |
| 5.5 Provides testing recommendations on which channels to test | 0 | 0.5 |
| 5.6 Provides test design recommendations | 0 | 0 |
| Category total | 0 / 6 | 2.5 / 6 |
Mutinex scores 0 across all six criteria in this category. The Mutinex platform does not include incrementality testing capabilities, and its conversational AI has no access to geo test results, A/B test results, or conversion lift test results. It does not summarize past tests, provide test design guidance, or recommend which channels to test. Mutinex's MMM is also not calibrated with incrementality tests, meaning that the model's channel attribution is not grounded in causal experiment evidence.
Sellforte scores 2.5 out of 6 in this category. This reflects the fact that Sellforte's broader incrementality testing platform capabilities are still being progressively integrated into the conversational AI interface, with full integration expected during 2026. The underlying Sellforte platform does cover geo tests, A/B tests, and conversion lift tests with a unified experiment library, and the MMM is calibrated with incrementality tests. Buyers who evaluate the broader Sellforte platform rather than just the current AI interface will find these capabilities available today.
6. Agentic Execution and Autonomy (Mutinex: 1/4, Sellforte: 2/4)
| Criterion | Mutinex | Sellforte |
|---|---|---|
| 6.1 AI can push budget and bidding changes to Meta, Google, and TikTok APIs | 0 | 0.5 |
| 6.2 AI's level of autonomy for execution can be configured | 0 | 0.5 |
| 6.3 AI has specialized agents for distinct workflows | 1 | 1 |
| 6.4 Proactive insights and alerts via AI | 0 | 0 |
| Category total | 1 / 4 | 2 / 4 |
Both platforms have limited agentic capabilities compared to the leaders in this category. Mutinex scores 1 out of 4, earning credit only for having specialized agents for distinct workflows rather than a single general-purpose chatbot. It does not push budget or bidding changes to ad platform APIs, does not offer configurable autonomy levels, and does not proactively surface anomalies or scheduled reports via Slack or email.
Sellforte scores 2 out of 4. It matches Mutinex on specialized agents, and partially supports ad platform API execution and configurable autonomy levels, with full autonomous agent capabilities yet to be announced. Neither platform currently offers proactive alerting via Slack or email through the conversational AI interface.
7. AI UX and Conversational Interface (Mutinex: 5/8, Sellforte: 6.5/8)
| Criterion | Mutinex | Sellforte |
|---|---|---|
| 7.1 Includes tables and charts inline in AI responses | 1 | 1 |
| 7.2 AI has conversation history and multi-turn context retention | 1 | 1 |
| 7.3 Allows convenient export of AI outputs (e.g., PDF, Slides, CSV) | 1 | 0.5 |
| 7.4 AI grounds answers in data, providing links from outputs to deep-dive dashboards | 0.5 | 1 |
| 7.5 AI operates in embedded and multi-window mode (chat and dashboard side-by-side) | 1 | 1 |
| 7.6 AI shows its reasoning steps and logic while answering | 0.5 | 1 |
| 7.7 AI handles non-English questions in production | 0 | 1 |
| 7.8 AI can be accessed via MCP server or external LLM | 0 | 0 |
| Category total | 5 / 8 | 6.5 / 8 |
Both platforms offer a strong conversational experience. Mutinex scores 5 out of 8, with inline tables and charts, multi-turn context retention, full export to PDF and Slides and CSV, and a side-by-side embedded mode. Its main gaps are partial coverage of data-grounded deep links from AI outputs and partial transparency on reasoning steps, and no verified production support for non-English queries.
Sellforte scores 6.5 out of 8. It includes inline charts and tables, multi-turn context retention, deep links from AI outputs into dashboards, side-by-side embedded mode, and reasoning steps shown while answering. It also supports at least five major languages in production, which is a significant differentiator for multi-country retail and ecommerce organizations. Both platforms currently lack MCP server access for external LLMs, and Sellforte's export to PDF and Slides is partially supported. Mutinex leads on export convenience; Sellforte leads on reasoning transparency, data grounding, and multilingual support.
8. Analytical Backbone (Mutinex: 2/4, Sellforte: 4/4)
| Criterion | Mutinex | Sellforte |
|---|---|---|
| 8.1 AI provides deterministic, model-backed answers with Bayesian MMM as backbone | 1 | 1 |
| 8.2 Bayesian MMM used by the AI is calibrated with incrementality tests | 0 | 1 |
| 8.3 AI reports model validation and other modelling KPIs | 1 | 1 |
| 8.4 Model calibration and configuration settings (e.g., priors) are auditable and editable in a self-serve UI | 0 | 1 |
| Category total | 2 / 4 | 4 / 4 |
Both platforms are built on Bayesian MMM and both report model validation KPIs, giving users some visibility into model quality. Beyond that, the gap is significant.
Mutinex scores 2 out of 4. Its MMM is not calibrated with incrementality tests, meaning that channel attribution is not grounded in causal experiment evidence. Model priors and configuration parameters are also not auditable or editable in a self-serve UI, making it difficult for data science and analytics teams to inspect or adjust the assumptions behind the AI's recommendations.
Sellforte scores a perfect 4 out of 4. Its Bayesian MMM is calibrated with incrementality tests, model validation KPIs are reported, and model priors and calibration parameters are inspectable and editable in a self-serve UI. For enterprise analytics teams that want to understand and configure the model driving the AI's recommendations, Sellforte is clearly the stronger choice.
9. Enterprise-Grade Platform (Mutinex: 4/7, Sellforte: 7/7)
| Criterion | Mutinex | Sellforte |
|---|---|---|
| 9.1 At least 10 public reference customers from $1B+ revenue brands | 1 | 1 |
| 9.2 SOC 2, ISO 27001, or audited IT security by a third-party cyber security auditor | 1 | 1 |
| 9.3 Data residency: geography option between US and EU | 0 | 1 |
| 9.4 Multi-cloud: option between AWS, GCP, and Azure | 0 | 1 |
| 9.5 Supports single sign-on (SSO) for enterprises | 1 | 1 |
| 9.6 Customer data is not shared to a third-party LLM (LLM deployed in customer-specific cloud container) | 1 | 1 |
| 9.7 Hands-on demo or trial of the AI is available without sales-call gating | 0 | 1 |
| Category total | 4 / 7 | 7 / 7 |
Mutinex performs reasonably well in this category, scoring 4 out of 7. It has 10 or more public reference customers from $1B+ revenue brands, holds SOC 2 or equivalent security certification, supports SSO for enterprise authentication, and runs LLM inference within isolated cloud infrastructure so customer data does not egress to third-party LLM APIs. These are meaningful enterprise credentials.
Sellforte scores a perfect 7 out of 7. In addition to matching Mutinex on all four criteria above, Sellforte offers US and EU data residency options, multi-cloud deployment across AWS, GCP, and Azure, and a publicly accessible hands-on demo of the AI without a sales call. The data residency and multi-cloud gaps are recurring procurement requirements in enterprise RFPs, particularly for multi-region or heavily regulated organizations. Advertisers operating under EU data governance requirements should verify whether the absence of a European data residency option is a blocker before committing to Mutinex.
Where Mutinex Wins
Mutinex's strongest area is channel-level optimization. It scores a perfect 5 out of 5 in that category, earning full credit for budget allocation recommendations, revenue forecasting, and advanced scenario planning. For organizations whose primary need is a conversational AI interface for channel-level spend optimization grounded in MMM, Mutinex delivers well.
Mutinex also performs strongly on historical performance insights, scoring 4 out of 5, and matches Sellforte on marketing data reporting. Its enterprise credentials, including large brand references, security certification, SSO, and isolated LLM infrastructure, make it a credible option for large organizations with standard IT requirements. Its export capabilities to PDF and Slides are also fully supported, which is a practical advantage for teams that regularly share AI outputs with stakeholders outside the platform.
Where Sellforte Wins
Sellforte's advantage is its campaign and ad set-level optimization and incrementality testing capabilities. Its analytical backbone is strong, with a fully calibrated Bayesian MMM with self-serve model configuration. It covers all nine evaluated categories with no zeroes,.
The gaps are most pronounced in three areas. On campaign and ad set-level optimization, Mutinex scores 0 out of 6 while Sellforte scores 4 out of 6. On incrementality testing, Mutinex scores 0 out of 6 while Sellforte scores 2.5 out of 6. On analytical backbone, Mutinex scores 2 out of 4 while Sellforte scores a perfect 4 out of 4. Sellforte also leads on enterprise requirements, multilingual support, reasoning transparency, and data-grounded deep links from AI outputs.
Which Should You Choose?
Choose Mutinex if: your primary need is a conversational AI interface for channel-level MMM-based spend optimization, you do not require campaign and ad set-level execution, incrementality testing is not part of your measurement program, and US/EU data residency and multi-cloud deployment are not procurement requirements. Mutinex is a reasonable fit for large enterprises with a mature channel-level MMM practice who want to make that MMM more accessible through a conversational interface.
Choose Sellforte if: you need campaign and ad set-level spend and bid optimization through the conversational AI, you run incrementality tests of any type and want them integrated into your measurement platform, and you want an MMM calibrated with incrementality tests. Sellforte also support multi-region data residency, multi-cloud deployment, and a self-serve model configuration UI.. Sellforte is also the stronger fit for retail and ecommerce organizations with large enterprise IT requirements or multi-country operations.
Frequently Asked Questions
What is Mutinex used for?
Mutinex is a Marketing Mix Modeling platform with a conversational AI interface called MAITE, built on its GrowthOS platform. Its primary use case is helping marketers optimize media spend allocation across channels through natural language. Mutinex does not cover campaign and ad set-level optimization, incrementality testing, or MMM calibration with experiments.
Does Mutinex support campaign and ad set-level optimization?
No. Based on our evaluation of publicly available documentation, Mutinex does not provide incremental ROAS, miROAS, spend recommendations, or bid recommendations at the campaign or ad set level. Its AI operates at the channel level only. Sellforte covers this level of optimization through its conversational AI interface.
Does Mutinex support incrementality testing?
No. Mutinex does not offer geo testing, A/B test analysis for owned media, or conversion lift test analysis. Its MMM is also not calibrated with incrementality tests. Organizations that want to ground their MMM in causal experiment evidence will need a different or additional solution.
What are the best Mutinex alternatives?
The closest alternatives depend on your priorities. Sellforte covers a broader set of capabilities including campaign-level optimization, incrementality testing, and a calibrated MMM. Lifesight is strong in channel-level optimization with a similar score to Mutinex in that category. Triple Whale leads on agentic execution and conversational UX, though with a lighter MMM. For teams specifically seeking incrementality testing platforms, Measured and Haus are also worth evaluating.
Is Mutinex good for enterprise?
Mutinex holds security certification, has strong $1B+ brand references, supports SSO, and isolates LLM inference from third-party APIs, making it credible for many enterprise buyers. However, it scores 4 out of 7 on our enterprise platform criteria. It does not offer US and EU data residency options or multi-cloud deployment across AWS, GCP, and Azure, which are common requirements in enterprise RFPs. Organizations with strict data governance requirements across multiple regions should verify whether these gaps create procurement blockers before committing to Mutinex.
How does Mutinex compare to Sellforte on channel-level optimization specifically?
Mutinex and Sellforte are close in this category, with Mutinex scoring 5 out of 5 versus Sellforte's 4.5 out of 5. Both platforms recommend optimal budget allocation by channel, forecast revenue under the recommended allocation, and support advanced scenario planning in natural language. Mutinex earns the slight edge by providing full coverage of miROAS and response curves per channel through its conversational AI interface. For buyers whose primary need is channel-level optimization, the difference between the two is small.
Is Mutinex's MMM calibrated with incrementality tests?
No. Based on publicly available information, Mutinex's Bayesian MMM is not calibrated with incrementality tests. This means that the model's channel attribution is not grounded in causal experiment evidence. Sellforte's MMM is calibrated with incrementality tests and includes a UI-based workflow for connecting experiment results to the model as calibration inputs.
Mutinex vs Sellforte: which is better for retail and ecommerce?
Sellforte is the stronger fit for retail and ecommerce organizations. Sellforte has been built specifically for retail and ecommerce, with enterprise reference customers including Lidl, C&A, Douglas, bonprix, and Tchibo. It covers offline store sales alongside ecommerce, supports campaign and ad set-level optimization relevant to performance marketing teams in these industries, and offers multilingual production support for multi-country retailers. Mutinex is a broader-market MMM platform and a reasonable alternative for retail organizations whose primary need is channel-level optimization.
Further Reading
7 Best AI Tools for MMM and Incrementality Testing in 2026: An In-Depth Comparison
The Rise of Agentic MMM: How AI Is Transforming Media Optimization
What is Incrementality Testing? Guide for Marketers
Marginal Incremental ROAS (miROAS): What is it? And why does it matter to marketers?
Commentary
Snapshot in time. Vendor capabilities evolve quickly. This comparison reflects publicly available information at the time of publication.
Corrections welcome. We will revise this comparison as new information becomes available. If a vendor believes a score is inaccurate, we welcome corrections with supporting documentation. Please email sales@sellforte.com.
Recommendation for buyers. Use this comparison as a structured starting point for your own evaluation, not as a final answer. We recommend conducting evaluation calls or demos with the vendors to verify fit against your organization's specific requirements.
Authors
Lauri Potka is the Chief Operating Officer at Sellforte, with over 15 years of experience in Marketing Mix Modeling, marketing measurement, and media spend optimization. Before joining Sellforte, he worked as a management consultant at the Boston Consulting Group, advising some of the world’s largest advertisers on data-driven marketing optimization. Follow Lauri in LinkedIn, where he is one of the leading voices in MMM and marketing measurement.
Emil Kauppi-Hoyer is Sellforte's Lead AI Engineer, leading the development of Sellforte AI. With a data science background, Emil belongs to Sellforte's engineering leadership. During his Sellforte career, Emil has implemented Marketing Mix Models and incrementality testing solutions to Sellforte's customers, while at the same time developing Sellforte's AI capabilities. Follow Emil in LinkedIn.
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Juha Nuutinen is the Chief Executive Officer and co-founder at Sellforte, with over 15 years of experience in optimizing marketing spend and promotional activity for the largest advertisers in the world. Before co-founding Sellforte, he worked as a management consultant at the Boston Consulting Group, specializing in promotion optimization. Follow Juha in LinkedIn, where he is actively sharing his views on marketing measurement.
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