Updated daily · Arena + Artificial Analysis
Call Transcripts & Long Context
Synthesizing a quarter of Gong/Granola calls, full CRM histories, or an entire content library in one pass.
One board from The GTM Model Leaderboard
Quick answer
For Call Transcripts & Long Context, Meta's Llama 4 Scout leads at 10M tokens Context window on the Artificial Analysis context window leaders, ahead of Grok 4.20 (0309). DemandLab recaptures this board daily; these numbers are from September 23, 2026. Rankings are job-specific, so the winner here is not the winner on the other seven boards.
Compiled by Chris Arden, Fractional CMO, DemandLab · Updated on
Call Transcripts & Long Context Leaderboard
Synthesizing a quarter of Gong/Granola calls, full CRM histories, or an entire content library in one pass.
- 1Llama 4 ScoutMeta10M tokensContext window
- 2Grok 4.20 (0309)xAI2M tokensContext window
- 3Gemini 1.5 Pro / 3 ProGoogle1-2M tokensContext window
- 4Claude Fable 5AnthropicStrong recall quality, Arena Longer Query #2 behind Opus 4.6 High1M tokensContext window
- 5Grok 4.6 (High)xAI32.3s time to first token, so batch it rather than sitting on it500K tokensContext window
Operator take · Raw window size is not recall quality. A 10M-token window that loses the middle of your call archive is worse than a 1M window that doesn't. These rows are held again rather than rewritten, for the fourth capture running, because the context-window card keeps returning different orderings below the top two and none of them has held long enough to publish. Llama 4 Scout at 10M and Grok 4.20 at 2M are the two constants across every read. What is independently confirmed today is the recall side: Opus 4.6 at high effort still ranks #1 on Arena's Longer Query board with Fable 5 at #2, and that is the number that actually predicts whether a long transcript survives the trip. Grok 4.6 keeps its slot at 500K, but note its 32-second time to first token: fine for an overnight transcript synthesis job, painful if you are waiting on it live. Test with a needle from your own transcripts before committing.
Updated daily from the linked public leaderboards; last capture September 23, 2026. Elo and win-rate figures are preference-based measures, not task-completion guarantees. Always validate the top pick on your own representative work before routing production volume to it.
How to Read These Rankings
Four rules before you switch models
- Every ranking is task-specific. The #1 agent model is not the #1 writer, and neither is the right pick for 10,000 Clay rows.
- Scores come from public leaderboards (Arena, Artificial Analysis) with capture dates shown. Preference Elo measures which output people like, not whether work gets completed.
- Reasoning effort and harness matter: the same model at a different effort tier or in a different agent harness ranks differently.
- Cheap plus fast beats frontier for volume work. Route by job, not by brand loyalty.
Frequently Asked Questions
Call Transcripts & Long Context: common questions
Which AI model is best for Call Transcripts & Long Context?
As of September 23, 2026, Llama 4 Scout from Meta ranks first for Call Transcripts & Long Context at 10M tokens Context window on the Artificial Analysis context window leaders. Grok 4.20 (0309) ranks second at 2M tokens, and Gemini 1.5 Pro / 3 Pro third at 1-2M tokens. DemandLab recaptures the board daily, so check the date above before quoting a position.
Where do these AI model rankings come from?
Call Transcripts & Long Context is scored from the Artificial Analysis context window leaders (https://artificialanalysis.ai/models), measured by Context window. DemandLab captures the public results, maps them to the go-to-market job they apply to, and publishes them unmodified. No scores are estimated, blended, or adjusted, and any board that cannot be read on a given day is left unchanged rather than guessed.
How often is the GTM Model Leaderboard updated?
Daily. The last capture was September 23, 2026. Model leaderboards move faster than most buying cycles, and positions inside a confidence interval can flip overnight, so DemandLab treats a single day's order as one observation rather than a trend.
Should I switch to the top-ranked model?
Not automatically. Raw window size is not recall quality. A 10M-token window that loses the middle of your call archive is worse than a 1M window that doesn't. These rows are held again rather than rewritten, for the fourth capture running, because the context-window card keeps returning different orderings below the top two and none of them has held long enough to publish. Llama 4 Scout at 10M and Grok 4.20 at 2M are the two constants across every read. What is independently confirmed today is the recall side: Opus 4.6 at high effort still ranks #1 on Arena's Longer Query board with Fable 5 at #2, and that is the number that actually predicts whether a long transcript survives the trip. Grok 4.6 keeps its slot at 500K, but note its 32-second time to first token: fine for an overnight transcript synthesis job, painful if you are waiting on it live. Test with a needle from your own transcripts before committing.
DemandLab routes these models inside production GTM systems every day. If you want help picking and wiring the right models into your own stack, that's what DemandLab does.