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Command R+ vs Pixtral Large

Pixtral Large leads the LLM Stats Score 11.8 to -0.5. Command R+ is 6.9x cheaper per token.

Cohere · Mistral AI · Updated for 2026

Which is better?

Pixtral Large leads the overall LLM Stats Score 11.8 to -0.5, ranking #262 overall.

On price, Command R+ is roughly 6.9x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose Command R+

  • cost matters — it's about 6.9x cheaper per token

Choose Pixtral Large

  • overall performance matters — it scores 11.8 and ranks #262 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you want the most recent training data — it shipped Nov 2024

At a glance

The differences that matter most.

Core performance indexes
-0.5
#334
11.8
#262
-0.8
#330
13.1
#246
Cost, coverage & limits
Benchmark wins
Input price
$0.25 / M
$2.00 / M
Output price
$1.00 / M
$6.00 / M
Context window
128,000
128,000

Individual benchmarks

6 reported for Command R+ · 7 for Pixtral Large

No common benchmarks found

Command R+ and Pixtral Largedon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

Command R+ costs less

For input processing, Command R+ ($0.25/1M tokens) is 8.0x cheaper than Pixtral Large ($2.00/1M tokens).

For output processing, Command R+ ($1.00/1M tokens) is 6.0x cheaper than Pixtral Large ($6.00/1M tokens).

In conclusion, Pixtral Large is more expensive than Command R+.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Sep 24 2026 • llm-stats.com
Cohere
Command R+
Input tokens$0.25
Output tokens$1.00
Best providerCohere
Mistral AI
Pixtral Large
Input tokens$2.00
Output tokens$6.00
Best providerMistral
Notice missing or incorrect data?Start an Issue

Model Size

Parameter count comparison

20.0B diff

Pixtral Large has 20.0B more parameters than Command R+, making it 19.2% larger.

Cohere
Command R+
104.0Bparameters
Mistral AI
Pixtral Large
124.0Bparameters
104.0B
Command R+
124.0B
Pixtral Large

Context Window

Maximum input and output token capacity

Both models have the same input context window of 128,000 tokens. Both models can generate responses up to 128,000 tokens.

Cohere
Command R+
Input128,000 tokens
Output128,000 tokens
Mistral AI
Pixtral Large
Input128,000 tokens
Output128,000 tokens
Thu Sep 24 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Pixtral Large supports multimodal inputs, whereas Command R+ does not.

Pixtral Large can handle both text and other forms of data like images, making it suitable for multimodal applications.

Command R+

Text
Images
Audio
Video

Pixtral Large

Text
Images
Audio
Video

License

Usage and distribution terms

Command R+ is licensed under CC BY-NC, while Pixtral Large uses Mistral Research License (MRL) for research; Mistral Commercial License for commercial use.

License differences may affect how you can use these models in commercial or open-source projects.

Command R+

CC BY-NC

Open weights

Pixtral Large

Mistral Research License (MRL) for research; Mistral Commercial License for commercial use

Open weights

Release Timeline

When each model was launched

Command R+ was released on 2024-08-30, while Pixtral Large was released on 2024-11-18.

Pixtral Large is 3 months newer than Command R+.

Command R+

Aug 30, 2024

2.1 years ago

Pixtral Large

Nov 18, 2024

1.8 years ago

2mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

Command R+ is available from Cohere, Bedrock. Pixtral Large is available from Mistral AI.

Command R+

cohere logo
Cohere
Input Price:Input: $0.25/1MOutput Price:Output: $1.00/1M
bedrock logo
AWS Bedrock
Input Price:Input: $3.00/1MOutput Price:Output: $15.00/1M

Pixtral Large

mistral logo
Mistral
Input Price:Input: $2.00/1MOutput Price:Output: $6.00/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against Command R+ and Pixtral Large side-by-side, then vote on the output you prefer.

Command R+
✓ Preferred
Pixtral Large
Open in Playground

FAQ

Common questions about Command R+ vs Pixtral Large.

Which is better, Command R+ or Pixtral Large?

Pixtral Large leads the LLM Stats Score 11.8 to -0.5. Command R+ is made by Cohere and Pixtral Large is made by Mistral AI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does Command R+ compare to Pixtral Large in benchmarks?

Command R+ scores HellaSwag: 88.6%, Winogrande: 85.4%, MMLU: 75.7%, ARC-C: 71.0%, GSM8k: 70.7%. Pixtral Large scores AI2D: 93.8%, DocVQA: 93.3%, ChartQA: 88.1%, VQAv2: 80.9%, MM-MT-Bench: 74.0%.

Is Command R+ cheaper than Pixtral Large?

Command R+ is 8.0x cheaper for input tokens. Command R+ costs $0.25/M input and $1.00/M output via cohere. Pixtral Large costs $2.00/M input and $6.00/M output via mistral.

What are the context window sizes for Command R+ and Pixtral Large?

Command R+ supports 128K tokens and Pixtral Large supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Command R+ and Pixtral Large?

Key differences include LLM Stats Score (-0.5 vs 11.8), input pricing ($0.25 vs $2.00/M), multimodal support (no vs yes), licensing (CC BY-NC vs Mistral Research License (MRL) for research; Mistral Commercial License for commercial use). See the full comparison above for benchmark-by-benchmark results.

Who makes Command R+ and Pixtral Large?

Command R+ is developed by Cohere and Pixtral Large is developed by Mistral AI.