Command R+
Not tested yet
Language modelActive
Command R+
Cohere
- Released
- April 2024
- Data date
- September 8, 2026
- Intelligence
- Overall score
- Price
- Input · Output / 1M tokens
- Input
- Text
- Output
- Text
No published category-wide ranking is available for this model.
Entries 1-12 of 42. Page 1 of 4.
Published benchmarks
Each chart compares models in the same documented test and highlights the current model.
GPQA Diamond
Overall
Higher is better54 modelsCommand R+: Rank 54 of 54Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-gpqa:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 54
- 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-2026-09-04-fc438726f0d8. Source payload hash: fc438726f0d8523d320f02d75ae372a3fa38b28b36f70fe318d119f55153560d. Parser version: vals-astro-v2. Imported at: 2026-09-04
LiveCodeBench v6
Overall
Higher is better56 modelsCommand R+: Rank 56 of 56Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-lcb:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 56
- 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-2026-09-04-95ca83387127. Source payload hash: 95ca83387127df287e9a6d928c411c98c9b65b4cefeee46eb4008ca1521f5ed4. Parser version: vals-astro-v2. Imported at: 2026-09-04
Legal
6 measurementsLegalBench
Conclusion Tasks
Higher is better2 modelsCommand R+: Rank 1 of 2Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-legal-bench:1:conclusion_tasks
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 2
- Methodology and context
- 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
LegalBench
Interpretation Tasks
Higher is better2 modelsCommand R+: Rank 1 of 2Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-legal-bench:1:interpretation_tasks
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 2
- Methodology and context
- 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
LegalBench
Issue Tasks
Higher is better2 modelsCommand R+: Rank 1 of 2Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-legal-bench:1:issue_tasks
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 2
- Methodology and context
- 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
LegalBench
Overall
Higher is better53 modelsCommand R+: Rank 49 of 53Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-legal-bench:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 53
- 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: 0.396. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-09-04-ff81649923fb. Source payload hash: ff81649923fb684ff37d5f557fd320ba5ab433927831065ed781a94548f480ef. Parser version: vals-astro-v2. Imported at: 2026-09-04
LegalBench
Rhetoric Tasks
Higher is better2 modelsCommand R+: Rank 1 of 2Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-legal-bench:1:rhetoric_tasks
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 2
- Methodology and context
- 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
LegalBench
Rule Tasks
Higher is better2 modelsCommand R+: Rank 1 of 2Data date: August 11, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-legal-bench:1:rule_tasks
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 2
- Methodology and context
- 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
MedQA
Overall
Higher is better27 modelsCommand R+: Rank 27 of 27Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-medqa:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 27
- 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-2026-09-04-de083a524dbf. Source payload hash: de083a524dbf0fa1c2da5cf0a06bd001693d2426690681ffac4cd93ccf3fbeba. Parser version: vals-astro-v2. Imported at: 2026-09-04
MMLU-Pro
Overall
Higher is better55 modelsCommand R+: Rank 55 of 55Data date: September 4, 2026
Scale: 0% - 100%
Methodology and context
- Comparison cohort
- vals-mmlu-pro:1:overall
- Metric
- accuracy
- Scale
- 0-100
- Participants
- 55
- 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-2026-09-04-94eef672a38c. Source payload hash: 94eef672a38c8146fc1334fecbd173c083343c88de0f3047ae7d034776227e0f. Parser version: vals-astro-v2. Imported at: 2026-09-04
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
Every observation retains its source value and published test conditions.
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
- 2026-09-04
- 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-2026-09-04-fc438726f0d8. Source payload hash: fc438726f0d8523d320f02d75ae372a3fa38b28b36f70fe318d119f55153560d. Parser version: vals-astro-v2. Imported at: 2026-09-04
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
- 2026-09-04
- 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-2026-09-04-95ca83387127. Source payload hash: 95ca83387127df287e9a6d928c411c98c9b65b4cefeee46eb4008ca1521f5ed4. Parser version: vals-astro-v2. Imported at: 2026-09-04
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: 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
- 2026-09-04
- 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: 0.396. Source ID: vals-ai. Evidence capture ID: vals-legal_bench-2026-09-04-ff81649923fb. Source payload hash: ff81649923fb684ff37d5f557fd320ba5ab433927831065ed781a94548f480ef. Parser version: vals-astro-v2. Imported at: 2026-09-04
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
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
- 2026-09-04
- 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-2026-09-04-de083a524dbf. Source payload hash: de083a524dbf0fa1c2da5cf0a06bd001693d2426690681ffac4cd93ccf3fbeba. Parser version: vals-astro-v2. Imported at: 2026-09-04
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
- 2026-09-04
- 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-2026-09-04-94eef672a38c. Source payload hash: 94eef672a38c8146fc1334fecbd173c083343c88de0f3047ae7d034776227e0f. Parser version: vals-astro-v2. Imported at: 2026-09-04
Our model tests
Community tests you can inspect
Compare how the models respond to the same prompt. Each test shows the first attempt, with no subsequent fixes to the generated code. These results do not contribute to an overall score.
Pelican on a bicycle
A community classic for free-form SVG drawing.
Prompt and test conditions
Generate an SVG of a pelican riding a bicycle
Token limit including reasoning: 8,192 tokens
Task origin (Simon Willison)Profile
Specifications and access
Published information about this model. Existing estimates are explicitly labeled.
Additional source observations
Dated documentation and model-card observations. Provider limits, native context and extended context can differ. Configuration notes retain the source wording.
- License
- CC-BY-NC-4.0Source
- Release
- 2024-04-04Source
- Parameters
- 104 BSource
- Architecture
- auto-regressive transformerSource
- Context window
- 128,000 tokensSource
- 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
Pricing
Published prices
Prices apply to the stated unit. Resolution, output length, and provider can change the cost.
Cost example
100 API requests
$0.75
100 requests with 1,000 input and 500 output tokens each calculate to $0.75. Input accounts for $0.25; output accounts for $0.5.
- Input price
- $2.5 / 1M tokensBase tier for each request
- Output price
- $10 / 1M tokensBase tier for each request
The calculation uses documented token prices and no cache discount. It excludes extra tools, tax, reasoning tokens, and further hidden output tokens.
Open sourceHead-to-head comparisons
Compare this model
Each matchup compares this model with exactly one other model from the same category.
There are no published direct comparisons for this model yet.
Evidence
Sources and data date
Every statement links to its underlying documentation or leaderboard.
- Price
Base API prices without caching or batch discounts. Higher context tiers and other rates are listed under Costs.
- Input
Documented modalities. Retrieved September 8, 2026.
- Output
Documented modalities. Retrieved September 8, 2026.
Research date September 8, 2026. 7 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication.
Open evidence questions and research notes (original wording)
Not found in the inspected sources
knowledge-cutoff. 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. The checked original sources do not publish a training-token count.
Unresolved
refresh-model-exclusion. 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. No exact Artificial Analysis model page located in the checked public sitemap.
- Model metadata (retrieved September 8, 2026)Source
- Context window dataSource
- API pricingSource
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Vals AI (retrieved August 11, 2026; September 4, 2026)Source
- Model metadata (retrieved September 8, 2026)Source
- Model metadata (retrieved September 8, 2026)Source
- Model metadata (retrieved September 8, 2026)Source
- Input (Model documentation)Source