The Inference Report

November 10, 2026

On SWE-rebench, the rankings remain stable with AnthropicFable 5 holding first place at 64.5% and confidence intervals narrow enough to distinguish the top tier from the rest, though the spread between positions one and five spans only 2.2 percentage points within overlapping error margins, making the practical gap between the highest performers modest. Artificial Analysis shows more movement: Claude Fable 5.2 enters at the top with 64.6, displacing Gemini 4 Carbon from first to second, and two new entries appear in the lower rankings (Muse Ember at position 17 and gpt-oss-120b at position 62), though these additions do not alter the standing of most existing models. The SWE-rebench benchmark measures code generation on real pull requests with controlled evaluation conditions, making it methodologically stronger than Artificial Analysis for assessing engineering capability, yet the consistency of top performers across both benchmarks suggests the ranking reflects genuine capability differences rather than benchmark-specific artifacts. Neither dataset shows the kind of discontinuous leap that would indicate a methodological shift or a fundamentally new approach to the problem; instead, the movement reflects incremental refinement and the introduction of new model variants within established families.

Cole Brennan

Daily rankings from SWE-rebench, a benchmark designed to fairly compare LLM capabilities on real-world software engineering tasks. Unlike other evaluations, it uses a standardized scaffolding for all models, continuously updates its dataset to prevent contamination, and runs each model five times to account for stochastic variance.

#ModelScore
1AnthropicFable 5 [high]Model64.5%± 1.41%
2GrokGrok 4.5 [high]Model63.8%± 0.60%
3AnthropicOpus 5 [high]Model63.4%± 1.35%
4Z.aiGLM-5.2 [high]Model62.9%± 1.19%
5OpenAIGPT-5.6 Sol [medium]Model62.3%± 1.83%
6JunieJunieAgent61.8%± 0.54%
7AnthropicClaude CodeAgent60.4%± 1.03%
8OpenAICodexAgent58.0%± 1.29%
9AnthropicSonnet 5 [high]Model56.8%± 0.94%
10CursorCursorAgent51.7%± 0.84%

Artificial Analysis composite index across coding, math, and reasoning benchmarks.

#ModelScoretok/s$/1M
1Claude Fable 5.264.695$16.00
2Gemini 4 Carbon60100$8.00
3Claude Opus 5.559.194$8.00
4GPT-6 Astra56.949$20.00
5GPT-6.1 Sol54.669$4.00
6Claude Sonnet 5.554.5128$4.00
7GPT-6.1 Terra51.3103$2.00
8Gemini 4 Argon50.489$8.00
9Muse Wonder Full50.1——
10Claude Fable 5.15059$20.00

Output tokens per second — higher is faster. Minimum intelligence score of 40.

#Modeltok/s
1GPT-6 Sol154
2Muse Wonder137
3Claude Sonnet 5.5128
4GPT-6.1 Terra103
5Gemini 4 Carbon100
6Claude Fable 5.295
7Claude Opus 5.594
8Gemini 4 Argon89
9GPT-6.1 Sol69
10Claude Fable 5.159

Blended cost per 1M tokens (3:1 input/output) — lower is cheaper. Minimum intelligence score of 40.

#Model$/1M
1GPT-6.1 Terra$2.00
2GPT-6.1 Sol$4.00
3Claude Sonnet 5.5$4.00
4Kimi K3.1 Pro$4.00
5GPT-6 Sol$4.00
6Gemini 4 Carbon$8.00
7Claude Opus 5.5$8.00
8Gemini 4 Argon$8.00
9Muse Wonder$8.00
10Claude Opus 5$10.00