Capability
47.6/100
field median 58.2
#142 of 218 ranked models
Command A+
Released May 20, 2026 — see all recent releases
Decision reading
Command A+ scores 47.6 out of 100 and ranks #142 of 218. This profile shows 4 source-displayable benchmark rows; its strongest eligible category is Multimodal & Grounded at #30. API pricing is $2.5 input and $10 output per million tokens.
Data as of August 15, 2026 · How the score is built
Strongest published evidence
Multimodal & Grounded ranks #30. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Validate before choosing
4 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #87.
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Price
$2.50input / $10 output
input median $1
blended $6.25
Speed
199tok/s
field median 94 tok/s
First token 10.46 s
Context
128Ktokens
field median 200,000
Reported for this model; direct source link not stored
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
Command A+ category percentile values
- Agentic33rd percentile
- CodingNot eligible
- ReasoningNot eligible
- KnowledgeNot eligible
- MathNot eligible
- MultilingualNot eligible
- Multimodal6th percentile
- Instruction followingNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#87/130
- CodingNot ranked
- ReasoningNot ranked
- KnowledgeNot ranked
- MathNot ranked
- MultilingualNot ranked
- Multimodal#30/32
- Inst. FollowingNot ranked
Top decileTop quartileMid-fieldNot eligible
What it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Current modelCommand A+ · 47.6 score · $6.25 blended per million tokens
Horizontal: blended price per million tokens, log scale · Vertical: public score
How much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic1/1 verified
- CodingNot measured
- ReasoningNot measured
- KnowledgeNot measured
- MathNot measured
- MultilingualNot measured
- Multimodal3/3 verified
- Inst. FollowingNot measured
Verified sourceProvisionalNot measured
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not published
- Context window
- 128K
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Not sourced yet
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing record
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersCategory score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #87 of 130Percentile 33rdWeight 22%1 benchmarkVerified | 44.2 | #87 of 130 | 33rd | 22% | 1 benchmark | Verified |
| CodingWeight 20%0 benchmarksNot measured | Not measured | Not ranked | Not available | 20% | 0 benchmarks | Not measured |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| 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 #30 of 32Percentile 6thWeight 12%3 benchmarksVerified | 8.0 | #30 of 32 | 6th | 12% | 3 benchmarks | Verified |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
Benchmark ledger
Agentic opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Agentic1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| τ²-bench resultsτ²-Bench Tool-Agent-User Evaluation | Score85% | Versus best verified row Best verified: GPT-5.4 · 98.9% | Gap13.9 behind | WeightDisplay only | Provider exact |
Multimodal3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMMU-ProMassive Multi-discipline Multimodal Understanding Pro | Score63% | Versus best verified row Best verified: GPT-5.4 Pro · 94% | Gap31 behind | WeightWeighted 45% | Provider exact |
| CharXivCharXiv Reasoning | Score52.7% | Versus best verified row Best verified: Claude Mythos 5 · 93.5% | Gap40.8 behind | WeightWeighted 25% | Provider exact |
| MMMUMassive Multi-discipline Multimodal Understanding | Score75.1% | Versus best verified row Best verified: Qwen3.6-27B · 82.9% | Gap7.8 behind | WeightDisplay only | Provider exact |
Lineage
The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
May 20, 2026 · you are here
Command A+Score 47.6 · $2.5 / $10
Plus
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Command A+ ranks #142 of 218 on the public leaderboard with a score of 47.56/100. It does not yet have enough sourced coverage for a verified position.
Command A+ is a open weight model with a 128K context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
4 of 437 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Multimodal & Grounded at #30, while its lowest eligible position is Agentic at #87. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Radar
Full release historyCommand A+ release history
Command A+ released
Cohere · Model release
Source confirmed
Frequently asked questions
How does Command A+ perform overall in AI benchmarks?
Command A+ ranks #142 out of 218 models on the public BenchAlign leaderboard, with a score of 47.56/100. Its evidence status is Estimated, and this profile shows 4 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Command A+ good for agentic tool use and computer tasks?
Command A+ ranks #87 out of 130 eligible models for agentic tool use and computer tasks, with a public category score of 44.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Command A+ good for multimodal and grounded tasks?
Command A+ ranks #30 out of 32 eligible models for multimodal and grounded tasks, with a public category score of 8/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Command A+ open source?
Command A+ is an open-weight model from Cohere. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Does Command A+ have full benchmark coverage on BenchLM?
No. Command A+ currently has 22 source-displayable rows across 437 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of Command A+?
Command A+ has a reported context window of 128K in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.
Last updated August 15, 2026. Runtime fields remain blank until a sourced snapshot exists.
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