Coding · Cohere

Command A Turbo on SWE-bench Verified: score, rank and what it means

Command A Turbo scores 67.2 on SWE-bench Verified, placing it #164 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
67.2
0–100 scale
Rank
#164
of 600
Percentile
73th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
14.5
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Command A Turbo highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Command A Turbo sits at #164 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 14.5 points. The median model in this index scores 61.0, which puts Command A Turbo above the midpoint.

Cohere models average 56.0 on this benchmark. Command A Turbo is 11.2 points above that provider line, so it is a stronger result than the average Cohere model.

Among multimodal models, the average is 66.4. Command A Turbo is 0.8 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 67.2 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $13.53 per million input tokens, Command A Turbo is above the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Sonar Pro Perplexity 65536 $11.25 77.1
GLM-4.5 Instruct Zhipu AI 200000 $4.70 78.8
Kimi K1.5 Base Moonshot AI 65536 $4.34 77.4
QwQ Instruct Alibaba Cloud 65536 $4.62 79.0
Command A Turbo Cohere 32768 $13.53 79.8
DeepSeek-Coder Instruct DeepSeek 32768 $4.34 77.7
Hunyuan-Turbo Reasoning Tencent 128000 $11.89 77.5

Other benchmarks for Command A Turbo

BenchmarkScoreRankPercentileRelative
MMLU-Pro 83.5 94 84th
GPQA Diamond 78.0 84 86th
HumanEval 83.4 148 75th
MATH-500 85.8 96 84th
AIME 2025 76.9 129 79th
LiveCodeBench 72.9 130 78th
IFEval 86.8 137 77th
TruthfulQA 81.4 144 76th
HellaSwag 86.9 180 70th
MMMU 75.4 152 75th
Arena Elo 1434.5 110 82th

FAQ

What score does Command A Turbo get on SWE-bench Verified?

Command A Turbo scores 67.2 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Command A Turbo rank on SWE-bench Verified?

It ranks #164 of 600 models, in the 73rd percentile. The leader is GPT-5.2 Pro at 81.7.

Is Command A Turbo good at SWE-bench Verified?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the SWE-bench Verified score calculated?

SWE-bench Verified is a coding benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Command A Turbo cost?

Command A Turbo costs $13.53 per million input tokens and $65.42 per million output tokens.

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