The Inference Report

October 16, 2026

The SWE-rebench rankings remain static across the top tier, with AnthropicFable 5 holding 64.5% and the top ten models unchanged, suggesting either stable evaluation conditions or that recent model releases haven't yet displaced the established leaders in coding task resolution. By contrast, Artificial Analysis shows substantial churn: Muse Spark Open enters at #34 with 55.8, pushing prior models down one position each; Solar Pro 4 drops from #67 to #75 despite unchanged performance at 26.6; Nemotron 3.5 Super VL and Nemotron 3.5 Bolt 74B-A9B appear as new entries at #76 and #124 respectively, while Gemma 3 12B Instruct falls dramatically from #472 to #475 with a score drop from 3.8 to 3.8, a data anomaly suggesting either scoring methodology change or evaluation inconsistency at the lower end. The coding benchmark shows no movement, which raises a methodological question: either the variance intervals (ranging from ±0.54% to ±1.83%) are wide enough to absorb real performance shifts, or the benchmark has reached saturation at the top where further differentiation is difficult. The Artificial Analysis churn at positions 34 and beyond appears driven by new model releases rather than score improvements in existing models, indicating the two benchmarks measure different capability dimensions or operate on different evaluation cadences. Without historical score changes for existing models in SWE-rebench, it's unclear whether the stability reflects genuine plateau or insufficient temporal resolution to detect drift.

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 Opus 5.557.698$8.00
2Claude Sonnet 5.556142$4.00
3Muse Wonder Full55.80$0.00
4Claude Fable 5.153.466$20.00
5GPT-6 Astra52.749$20.00
6Gemini 4 Argon52.60$4.00
7Muse Wonder52.4174$8.00
8GPT-6.1 Sol51.859$4.00
9Claude Opus 550.80$10.00
10Claude Fable 549.60$20.00

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

#Modeltok/s
1Claude Haiku 5.5235
2Ling 3.1 Flash217
3Muse Wonder174
4Claude Sonnet 5.5142
5Gemini 3.8 Flash136
6Muse Spark 1.3135
7GPT-5.6 Terra116
8Claude Opus 5.598
9Step 5 Preview86
10Grok 4.783

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

#Model$/1M
1Claude Haiku 5.5$0.20
2GLM-5.3-Flash$0.237
3Ling 3.1 Flash$0.45
4MiMo-V2.6-Pro$0.544
5Step 5 Preview$1.43
6Gemini 3.8 Flash$1.50
7Muse Spark 1.3$2.00
8GLM-5.3$2.15
9Grok 4.7$3.00
10Qwen3.8 Max$3.00