Command R+
Cohere
- Released
- April 2024
- Data date
- September 8, 2026
- Intelligence
- Overall score
- Input
- Text
- Output
- Text
Command R+ carries the original Command R approach into a larger model class with 104 billion parameters, ten languages, and a 128,000-token context. Cohere built the checkpoint for more demanding RAG work and multi-step tool use. Its size was the main distinction from the smaller Command R.
Cohere identifies this model as command-r-plus-04-2024. The API alias has been deprecated since September 15, 2025. The command-r-plus-08-2024 update remains a separate checkpoint. The open weights use CC-BY-NC-4.0 and remain subject to the documented usage terms.
- Position
- Rank 85 of 86
- Index score
- 2.5 / 100
Methodology and source
The index averages rank percentiles from 10 documented comparison cohorts.
Page 1 of 4
Published benchmarks
GPQA Diamond
Overall
higher is betterAs of September 29, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-gpqa:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 76
- Methodology and context
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 8.194. Cost per task in USD: 0.007438. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-09-29-8caf7b4807e8. Source payload hash: 8caf7b4807e87a2880c30218acea7855ea3a11721d56f7e049a77fadaf35dd34. Parser version: vals-astro-v2. Imported at: 2026-09-29
LiveCodeBench v6
Overall
higher is betterAs of September 29, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-lcb:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 77
- Methodology and context
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 5.463. Cost per task in USD: 0.003267. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-09-29-b6ee1006a41a. Source payload hash: b6ee1006a41aab0c68eef9d3e42a2151634fffaaeb6bdc2230a6d02994198a59. Parser version: vals-astro-v2. Imported at: 2026-09-29
Legal
LegalBench
| Sub-task | Command R+ (This model) | Command R |
|---|---|---|
| Conclusion Tasks | 48.31% (best value in this row) | 13.98% |
| Interpretation Tasks | 71.62% (best value in this row) | 38.72% |
| Issue Tasks | 76.32% (best value in this row) | 8.89% |
| Rhetoric Tasks | 75.64% (best value in this row) | 71.01% |
| Rule Tasks | 69.55% (best value in this row) | 32.24% |
higher is betterAs of August 11, 2026Source: Vals AIbars scaled within each row, not across rows
Methodology and context
- Metric
- accuracy
LegalBench
Overall
higher is betterAs of September 29, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-legal-bench:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 78
- Methodology and context
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-27. Latency in seconds: 0.396. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-09-29-c1213019b552. Source payload hash: c1213019b55234a262ae86fd4ebfe291530f315c988a4ee32fd501c13777f85f. Parser version: vals-astro-v2. Imported at: 2026-09-29
MedQA
Overall
higher is betterAs of September 29, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-medqa:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 39
- Methodology and context
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-04-16. Latency in seconds: 6.056. Cost per task in USD: 0.003456. Source ID: vals-ai. Evidence capture ID: vals-medqa-2026-09-29-2886a92806d7. Source payload hash: 2886a92806d7b2e892c96203b7c7b462a4e28ec54dae900401734c38aa443883. Parser version: vals-astro-v2. Imported at: 2026-09-29
MMLU-Pro
Overall
higher is betterAs of September 29, 2026Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-mmlu-pro:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 77
- Methodology and context
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 4.419. Cost per task in USD: 0.00566. Source ID: vals-ai. Evidence capture ID: vals-mmlu_pro-2026-09-29-383f4d5d1419. Source payload hash: 383f4d5d141971e7bb60b6c77a0df7a2be27ee6a005dd8854eb2df953dec36a4. Parser version: vals-astro-v2. Imported at: 2026-09-29
Measurements without matching peer values
These measurements have no matching peer values under the same test conditions. Their original values and sources remain available here.
GPQA Diamond: Few-Shot CoT (Show measurement, test conditions, and source)
- Source value
- 28.283
- Score
- 28.283
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- reasoning
- Task
- diamond_few_shot_cot
- Task label
- Few-Shot CoT
- Direction
- Higher is better
- Comparison cohort
- vals-gpqa:1:diamond_few_shot_cot
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Provider reported by source: Cohere. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Temperature: 0.3. Maximum output tokens: 4000. Latency in seconds: 8. Standard error: 3.183. Cost per task in USD: 0.009178. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-08-11-d3325290a404. Source payload hash: d3325290a40411054e05ecb86812143465b4d8eee24a0f71f6cf5dfee5b232a1. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 0.3. Maximum output tokens: 4000
GPQA Diamond: Zero-Shot CoT (Show measurement, test conditions, and source)
- Source value
- 33.838
- Score
- 33.838
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- reasoning
- Task
- diamond_zero_shot_cot
- Task label
- Zero-Shot CoT
- Direction
- Higher is better
- Comparison cohort
- vals-gpqa:1:diamond_zero_shot_cot
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Provider reported by source: Cohere. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Temperature: 0.3. Maximum output tokens: 4000. Latency in seconds: 8.387. Standard error: 3.266. Cost per task in USD: 0.005699. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-08-11-d3325290a404. Source payload hash: d3325290a40411054e05ecb86812143465b4d8eee24a0f71f6cf5dfee5b232a1. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 0.3. Maximum output tokens: 4000
Recorded measurement details
GPQA Diamond: Overall (Show measurement, test conditions, and source)
- Source value
- 31.06
- Score
- 31.06
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- reasoning
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-gpqa:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-29
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 8.194. Cost per task in USD: 0.007438. Source ID: vals-ai. Evidence capture ID: vals-gpqa-2026-09-29-8caf7b4807e8. Source payload hash: 8caf7b4807e87a2880c30218acea7855ea3a11721d56f7e049a77fadaf35dd34. Parser version: vals-astro-v2. Imported at: 2026-09-29
LiveCodeBench v6: Overall (Show measurement, test conditions, and source)
- Source value
- 18.238
- Score
- 18.238
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- coding
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-lcb:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-29
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 5.463. Cost per task in USD: 0.003267. Source ID: vals-ai. Evidence capture ID: vals-lcb-2026-09-29-b6ee1006a41a. Source payload hash: b6ee1006a41aab0c68eef9d3e42a2151634fffaaeb6bdc2230a6d02994198a59. Parser version: vals-astro-v2. Imported at: 2026-09-29
LegalBench: Conclusion Tasks (Show measurement, test conditions, and source)
- Source value
- 48.306
- Score
- 48.306
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- legal
- Task
- conclusion_tasks
- Task label
- Conclusion Tasks
- Direction
- Higher is better
- Comparison cohort
- vals-legal-bench:1:conclusion_tasks
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Provider reported by source: Cohere. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Temperature: 0.3. Maximum output tokens: 4000. Latency in seconds: 0.238. Standard error: 1.196. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-08-11-836e5e44618e. Source payload hash: 836e5e44618e5bb1564702e615e2a5d9f70e26300758fa7cf8bad50033a889bb. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 0.3. Maximum output tokens: 4000
LegalBench: Interpretation Tasks (Show measurement, test conditions, and source)
- Source value
- 71.624
- Score
- 71.624
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- legal
- Task
- interpretation_tasks
- Task label
- Interpretation Tasks
- Direction
- Higher is better
- Comparison cohort
- vals-legal-bench:1:interpretation_tasks
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Provider reported by source: Cohere. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Temperature: 0.3. Maximum output tokens: 4000. Latency in seconds: 0.239. Standard error: 0.237. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-08-11-836e5e44618e. Source payload hash: 836e5e44618e5bb1564702e615e2a5d9f70e26300758fa7cf8bad50033a889bb. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 0.3. Maximum output tokens: 4000
LegalBench: Issue Tasks (Show measurement, test conditions, and source)
- Source value
- 76.319
- Score
- 76.319
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- legal
- Task
- issue_tasks
- Task label
- Issue Tasks
- Direction
- Higher is better
- Comparison cohort
- vals-legal-bench:1:issue_tasks
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Provider reported by source: Cohere. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Temperature: 0.3. Maximum output tokens: 4000. Latency in seconds: 0.318. Standard error: 0.708. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-08-11-836e5e44618e. Source payload hash: 836e5e44618e5bb1564702e615e2a5d9f70e26300758fa7cf8bad50033a889bb. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 0.3. Maximum output tokens: 4000
LegalBench: Rhetoric Tasks (Show measurement, test conditions, and source)
- Source value
- 75.635
- Score
- 75.635
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- legal
- Task
- rhetoric_tasks
- Task label
- Rhetoric Tasks
- Direction
- Higher is better
- Comparison cohort
- vals-legal-bench:1:rhetoric_tasks
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Provider reported by source: Cohere. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Temperature: 0.3. Maximum output tokens: 4000. Latency in seconds: 0.247. Standard error: 0.842. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-08-11-836e5e44618e. Source payload hash: 836e5e44618e5bb1564702e615e2a5d9f70e26300758fa7cf8bad50033a889bb. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 0.3. Maximum output tokens: 4000
LegalBench: Rule Tasks (Show measurement, test conditions, and source)
- Source value
- 69.553
- Score
- 69.553
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- legal
- Task
- rule_tasks
- Task label
- Rule Tasks
- Direction
- Higher is better
- Comparison cohort
- vals-legal-bench:1:rule_tasks
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-08-11
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Provider reported by source: Cohere. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-08-09. Temperature: 0.3. Maximum output tokens: 4000. Latency in seconds: 0.94. Standard error: 2.805. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-08-11-836e5e44618e. Source payload hash: 836e5e44618e5bb1564702e615e2a5d9f70e26300758fa7cf8bad50033a889bb. Parser version: vals-astro-v2. Imported at: 2026-08-11
- Comparison methodology
- Temperature: 0.3. Maximum output tokens: 4000
LegalBench: Overall (Show measurement, test conditions, and source)
- Source value
- 68.287
- Score
- 68.287
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- legal
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-legal-bench:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-29
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-27. Latency in seconds: 0.396. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-09-29-c1213019b552. Source payload hash: c1213019b55234a262ae86fd4ebfe291530f315c988a4ee32fd501c13777f85f. Parser version: vals-astro-v2. Imported at: 2026-09-29
MedQA: Overall (Show measurement, test conditions, and source)
- Source value
- 2.651
- Score
- 2.651
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- health
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-medqa:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-29
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-04-16. Latency in seconds: 6.056. Cost per task in USD: 0.003456. Source ID: vals-ai. Evidence capture ID: vals-medqa-2026-09-29-2886a92806d7. Source payload hash: 2886a92806d7b2e892c96203b7c7b462a4e28ec54dae900401734c38aa443883. Parser version: vals-astro-v2. Imported at: 2026-09-29
MMLU-Pro: Overall (Show measurement, test conditions, and source)
- Source value
- 44.003
- Score
- 44.003
- Metric
- accuracy
- Unit
- %
- Benchmark version
- 1
- Category
- knowledge
- Task
- overall
- Task label
- Overall
- Direction
- Higher is better
- Comparison cohort
- vals-mmlu-pro:1:overall
- Source type
- independent-evaluator
- Evaluator
- Vals AI
- Status
- active
- Retrieved at
- 2026-09-29
- Methodology
- Source model ID: cohere/command-r-plus. Source model name: Command R+. Evaluator: Vals AI. Dataset type: public. Leaderboard date: 2026-09-01. Latency in seconds: 4.419. Cost per task in USD: 0.00566. Source ID: vals-ai. Evidence capture ID: vals-mmlu_pro-2026-09-29-383f4d5d1419. Source payload hash: 383f4d5d141971e7bb60b6c77a0df7a2be27ee6a005dd8854eb2df953dec36a4. Parser version: vals-astro-v2. Imported at: 2026-09-29
Page 1 of 4
Popularity
19.1 / 100
Specifications and access
| Specification | Value and source |
|---|---|
| Weights | Open weightsSource |
| Access | LocalSource |
| Parameters | 104BSource |
| Context window | 128,000 tokensSource |
| License | CC-BY-NC-4.0Source |
| Release | 2024-04-04Source |
| Parameters | 104 BSource |
| Architecture | auto-regressive transformerSource |
| Maximum output | 4,000 tokensSource |
| Input | TextSource |
| Output | TextSource |
| Languages | 10Source |
| Tool calling | YesSource |
| API model ID | command-r-plus-04-2024Source |
| Model revision release | 2024-08-30 (This dates the separate command-r-plus-08-2024 refresh and is not an original Command R+ release date.)Source |
Predecessor and successor
- Later model generation
- Command R+ 08-2024 (Official documentation)
Official documentation
Model lineage evidence
Cohere's own changelog announces updates to its flagship generative AI model series, Command R and Command R+, giving the refreshed models' throughput and latency relative to the previous version; it does not use the words replaces or successor, so this is recorded as nearest-profile rather than direct.
Cohere changelog: Command models August refresh (2026-09-19)
Sources and data date
| Type | Evidence and data date |
|---|---|
| Input | Documented modalities. Retrieved September 8, 2026. |
| Output | Documented modalities. Retrieved September 8, 2026. |
| Research status | Research date September 8, 2026. 7 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication. |
| Not found in the inspected sources | knowledge-cutoff Original wording The checked original card, launch post and model overview do not publish an exact cutoff for command-r-plus-04-2024. |
| Not found in the inspected sources | training-tokens Original wording The checked original sources do not publish a training-token count. |
| Unresolved | refresh-model-exclusion Original wording Earlier evidence used the same canonical ID for the August 2024 refresh. The refresh is a separate command-r-plus-08-2024 model and its facts and benchmarks are intentionally excluded from this original record. |
| Unresolved | AA benchmark rows Original wording No exact Artificial Analysis model page located in the checked public sitemap. |
| Additional source | Model metadata (retrieved September 8, 2026) · Cohere Command R and R+ model card · Editorial description reviewed October 2, 2026 |
| Additional source | Provider model lifecycle (retrieved October 2, 2026) · Cohere model overview and lifecycle · Editorial description reviewed October 2, 2026 |
| Additional source | Vals AI (retrieved August 11, 2026; September 29, 2026) |
| Additional source | Vals AI (retrieved August 11, 2026; September 29, 2026) |
| Additional source | Vals AI (retrieved August 11, 2026; September 29, 2026) |
| Additional source | Vals AI (retrieved August 11, 2026; September 29, 2026) |
| Additional source | Vals AI (retrieved August 11, 2026; September 29, 2026) |
| Additional source | Model metadata (retrieved September 8, 2026) |
| Additional source | Model metadata (retrieved September 8, 2026) |
| Additional source | Model metadata (retrieved September 8, 2026) |
| Additional source | Cohere Command R+ documentation · Editorial description reviewed October 2, 2026 |
| Additional source | OpenRouter: Popularity index (derived), CC BY 4.0 |
| Additional source | Vercel AI Gateway: Popularity index (derived), CC BY 4.0 |
| Additional source | Creative Commons Attribution 4.0 |
| Additional source | Cohere changelog: Command models August refresh (2026-09-19) |