Model profile
Command A+
Evidence coverage
21 of 323 tracked benchmarks are published. 4 are verified and 17 provisional. 6 of 8 categories are measured.
- Published / tracked
- 21 / 323
- Verified
- 4
- Provisional
- 17
- Categories with evidence
- 6 / 8
Evidence by category
- Agentic5 benchmarksMixed evidence
- Coding2 benchmarksReported
- Reasoning2 benchmarksReported
- Knowledge7 benchmarksReported
- Math0 benchmarksNot measured
- Multilingual0 benchmarksNot measured
- Multimodal4 benchmarksMixed evidence
- Inst. Following1 benchmarkReported
Command A+ ranks #135 out of 200 models on the public leaderboard with an overall score of 47.51/100. It does not yet have enough sourced coverage for BenchLM's verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
Command A+ is a open weight model with a 128K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.
This profile currently has 21 of 323 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Multimodal & Grounded (#27), while its weakest is Coding (#113). This performance profile makes it particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 47.2–47.74
- Claude 3.5 SonnetAnthropicCompare#13247.74Claude 3.5 Sonnet is #132 with a score of 47.74.
- GLM-4.5-AirZ.AICompare#13347.7GLM-4.5-Air is #133 with a score of 47.7.
- Qwen3.5 FlashAlibabaCompare#13447.65Qwen3.5 Flash is #134 with a score of 47.65.
- Command A+Current modelCohere#13547.51Command A+ is #135 with a score of 47.51.
- o3-miniOpenAICompare#13647.41o3-mini is #136 with a score of 47.41.
- Gemma 4 12BGoogleCompare#13747.29Gemma 4 12B is #137 with a score of 47.29.
- Qwen3.5 PlusAlibabaCompare#13847.2Qwen3.5 Plus is #138 with a score of 47.2.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
- Multimodal7%Eligible cohort rank #27 of 29Category score 7.0
- Agentic31%Eligible cohort rank #83 of 119Category score 43.8
- Coding7%Eligible cohort rank #113 of 122Category score 35.4
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #83 of 119Percentile 31stWeight 22%5 benchmarksMixed sources | 43.8 | #83 of 119 | 31st | 22% | 5 benchmarks | Mixed sources |
| CodingRank #113 of 122Percentile 7thWeight 20%2 benchmarksReported | 35.4 | #113 of 122 | 7th | 20% | 2 benchmarks | Reported |
| ReasoningWeight 17%2 benchmarksReported | Score pending | Not ranked | Not available | 17% | 2 benchmarks | Reported |
| KnowledgeWeight 12%7 benchmarksReported | Score pending | Not ranked | Not available | 12% | 7 benchmarks | Reported |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalRank #27 of 29Percentile 7thWeight 12%4 benchmarksMixed sources | 7.0 | #27 of 29 | 7th | 12% | 4 benchmarks | Mixed sources |
| Inst. FollowingWeight 5%1 benchmarkReported | Score pending | Not ranked | Not available | 5% | 1 benchmark | Reported |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Agentic5 benchmarks
τ²-Bench Tool-Agent-User Evaluation
Artificial Analysis Agentic Index
GDPval-AA normalized
Coding2 benchmarks
Artificial Analysis Coding Index
Artificial Analysis SciCode
Reasoning2 benchmarks
Artificial Analysis Long Context Reasoning
Critical Physics Tasks
Knowledge7 benchmarks
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Artificial Analysis Omniscience Index
Artificial Analysis Omniscience Accuracy
Artificial Analysis Omniscience Hallucination Rate
Artificial Analysis Openness Index
Multimodal4 benchmarks
Massive Multi-discipline Multimodal Understanding Pro
CharXiv Reasoning
Massive Multi-discipline Multimodal Understanding
Artificial Analysis MMMU-Pro
Inst. Following1 benchmark
Artificial Analysis IFBench
Frequently Asked Questions
How does Command A+ perform overall in AI benchmarks?
Command A+ has 21 published benchmark scores on BenchLM, but it does not yet have enough non-generated coverage to receive a global overall rank.
Is Command A+ good for knowledge and understanding?
Command A+ has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is Command A+ good for coding and programming?
Command A+ ranks #113 out of 122 models in coding and programming benchmarks with an average score of 35.4. There are stronger options in this category.
Is Command A+ good for reasoning and logic?
Command A+ has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is Command A+ good for agentic tool use and computer tasks?
Command A+ ranks #83 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 43.8. There are stronger options in this category.
Is Command A+ good for multimodal and grounded tasks?
Command A+ ranks #27 out of 29 models in multimodal and grounded tasks benchmarks with an average score of 7. There are stronger options in this category.
Is Command A+ good for instruction following?
Command A+ has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.
Is Command A+ open source?
Yes, Command A+ is an open weight model created by Cohere, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does Command A+ have full benchmark coverage on BenchLM?
Not yet. Command A+ currently has 21 published benchmark scores out of the 323 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of Command A+?
Command A+ has a published context window of 128K, which determines how much text it can process in a single interaction.
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