New SOTA. 13.1pp above Opus 4.6 (80.8%). Largest single-generation coding jump in Anthropic history.

Updated official score with prompt modification, averaged over 25 trials. Previous entry was 80.8%.

First model to exceed 80% on SWE-bench Verified. 25 trials avg.

Agentic coding benchmark. Verified from official Gemini page.

MoE 230B params, 10B active. Matches Claude Opus 4.6 speed on SWE-Bench eval.

Multi-language bug fixing. SWE-bench Pro score: 55.6% (new SOTA).

OpenAI coding-focused model. Also scores 56.8% on SWE-bench Pro (harder multilingual variant).

79.6% on SWE-bench Verified, 1.2 points behind Opus 4.6, surpasses Sonnet 4.5 by 2.4 points

Qwen 3.6 Plus scores 78.8% on SWE-bench Verified

Distilled model outperforms Gemini 3 Pro (76.2%) on agentic coding. Less than a quarter the cost of Pro.

Leading open-model score. Only 3 points behind Opus 4.6. Terminal-Bench 2.0: 56.2%.

Grok bot relayed Zhipu GLM-5.1 score; no direct link to paper or official source

First model from Meta Superintelligence Labs. Competitive with Gemini 3.1 Pro on agentic coding.

77.2% standard, 78.2% with 1M context, 82.0% with parallel compute. SOTA at time of release.

Independent Vals.ai evaluation. OpenAI dropped SWE-bench Verified in favor of SWE-bench Pro (57.7%).

1T MoE open-source. Competitive with Claude Sonnet 4.6 (79.6). Uses internal eval framework with bash/createfile tools.

Competitive with Claude Sonnet 4.5 and DeepSeek V3.2 on coding tasks.

Strong open-weight coding performance. 17B active params, MoE architecture.

Below GPT-5.4 (77.2%) and Claude Opus 4.6 (81.4%). Coding was not GPT-5 main strength.

Third-party harness engineering by Fujitsu. Test-time scaling with 8 candidate patches, no fine-tuning. Highest score among <229B param models.

Open-weight MoE with only 11B active params. Competitive with proprietary mid-tier models on coding.

Top tier with Claude/GPT. Fast inference + huge context.

Open-weight, 400B params. Strong coding for an open model but behind GLM-5/5.1 successors.

Near Pro level (76.5) at roughly half the cost.

Anthropic first Haiku with extended thinking. Matches Sonnet 4 on coding at 1/3 cost.

Primary score from DeepSeek technical report. Robustness tests across frameworks range 72-74%. Trails Claude Opus 4.6 (80.8%) and GPT-5.3 Codex (80.0%).

Grok bot stated ~70-75% range; midpoint used; no official xAI source linked

Open-weight 27B dense model matching GPT-5 mini. Released Feb 2026.

123B dense transformer, 256k context. Best open-weight SWE-bench score. 7x more cost-efficient than Claude Sonnet.

Solid coding ability. Behind frontier models (Claude Opus 4.6 at 81.4%, Gemini 3.1 Pro at 80.6%).

80B MoE, only 3B active params. Coding specialist matching models 10-20x larger.

17B MoE with 128 experts. Strong coding performance for open-weight model, competitive with GPT-4o class.

Cost-efficient reasoning model. Behind o3 (69.1%) but far ahead of o1 (48.9%) and o3-mini (49.3%).

24B open-weight coding model. Runs locally on RTX 4090. Apache 2.0 license.

Evaluated with mini-swe-agent-v2. Behind closed-source leaders but competitive for open-weight.

OpenAI's first open-weight model at 116.8B params (5.1B active). Apache 2.0 license. High reasoning effort.

20.9B total params (3.6B active). Runs on 16GB consumer hardware. Apache 2.0. Impressive for its size — near gpt-oss-120b SWE-bench score.

Lightweight MoE flash variant. Solid for its size class.

Independent vals.ai test. Significant gap from xAI self-reported 72-75%, highlighting scaffold sensitivity.

India's first domestically-trained 105B model. MoE with 10.3B active params. Apache 2.0.