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Comparison · 3 models · Updated Nov 2, 2026

Pixtral Large (25.02) vs Command R+ vs Gemini 2.5 Pro Preview 06-05

Gemini 2.5 Pro Preview 06-05 comes out ahead, 48 to 33 and 25 on our weighted score, though Pixtral Large (25.02) is 10% cheaper per token.

  1. Mistral AI

    Pixtral Large (25.02)

    Released Apr 8, 2025

    33/100
    • ECI—
    • Price$2.00 / $6.00
    • Context128K
  2. Cohere

    Command R+

    Released Aug 30, 2024

    25/100
    • ECI—
    • Price$2.50 / $10.00
    • Context128K
  3. Our pick

    Google

    Gemini 2.5 Pro Preview 06-05

    Released Jun 5, 2025

    48/100
    • ECI—
    • Price$1.22 / $9.75
    • Context1.05M
01 — Verdict

Gemini 2.5 Pro Preview 06-05 is our pick

Gemini 2.5 Pro Preview 06-05 is the better all-round choice, scoring 48/100 against Pixtral Large (25.02) (33) and Command R+ (25). It leads on inputs & features and context window. Pixtral Large (25.02) wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

  • CapabilityNot enough dataNo independent benchmark covers every model here yet
  • Lowest pricePixtral Large (25.02)Pixtral Large (25.02) $3.00 · Gemini 2.5 Pro Preview 06-05 $3.35 · Command R+ $4.38 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 Pro Preview 06-05Gemini 2.5 Pro Preview 06-05 1,048,576 · Pixtral Large (25.02) 128,000 · Command R+ 128,000 tokens
  • Widest inputsGemini 2.5 Pro Preview 06-05Pixtral Large (25.02): Text, Images · Command R+: Text · Gemini 2.5 Pro Preview 06-05: Text, Images, PDFs, Audio
  • Self-hostingCommand R+Publishes downloadable weights
How the score is built
MeasureWeightPixtral Large (25.02)Command R+Gemini 2.5 Pro Preview 06-05
Price50%261924
Inputs & features30%503580
Context window20%242461
Overall100%33/10025/10048/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Pixtral Large (25.02) vs Command R+ vs Gemini 2.5 Pro Preview 06-05 specifications side by side
SpecificationPixtral Large (25.02)Mistral AICommand R+CohereGemini 2.5 Pro Preview 06-05Google
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$2.00$2.50$1.22 (best)
Output$6.00 (best)$10.00$9.75
Cached input———
Blended (3:1)$3.00 (best)$4.38$3.35
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 3 providersOfficial Cohere APIMedian of 4 providers
Limits
Context window128,000 tokens128,000 tokens1,048,576 tokens (best)
Max output8,192 tokens4,000 tokens65,536 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsNoNoYes
AudioNoNoYes
VideoNoNoNo
ReasoningNoNoYes
Tool callingYesYesYes
Structured outputNoYesNo
Availability
WeightsProprietaryOpenProprietary
API model ID—command-r-plus-08-2024—
API providers38 (best)4
ReleasedApr 8, 2025Aug 30, 2024Jun 5, 2025
Knowledge cutoff—Jun 1, 2024Jan 31, 2025
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • Pixtral Large (25.02)$32.00
  • Command R+$45.00
  • Gemini 2.5 Pro Preview 06-05$31.69
04 — Questions

Which should you choose?

Which is better: Pixtral Large (25.02), Command R+ or Gemini 2.5 Pro Preview 06-05?

Gemini 2.5 Pro Preview 06-05 is the better all-round choice, scoring 48/100 against Pixtral Large (25.02) (33) and Command R+ (25). It leads on inputs & features and context window. Pixtral Large (25.02) wins on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.

Which is cheaper, Pixtral Large (25.02), Command R+ or Gemini 2.5 Pro Preview 06-05?

Pixtral Large (25.02) is cheaper at $2.00 input / $6.00 output per million tokens (median across 3 API providers). Gemini 2.5 Pro Preview 06-05 costs $1.22 input / $9.75 output per million tokens (median across 4 API providers); Command R+ costs $2.50 input / $10.00 output per million tokens (official Cohere API price). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Pixtral Large (25.02) versus $3.35 for Gemini 2.5 Pro Preview 06-05 (1.1× as much) and $4.38 for Command R+ (1.5× as much).

Which scores higher on benchmarks?

There is no independent benchmark that covers all three models yet. Pixtral Large (25.02) has not been scored yet, Command R+ has not been scored yet and Gemini 2.5 Pro Preview 06-05 has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Pixtral Large (25.02), Command R+ and Gemini 2.5 Pro Preview 06-05 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.

Which has the bigger context window?

Gemini 2.5 Pro Preview 06-05 has the largest context window at 1,048,576 tokens, against 128,000 for Pixtral Large (25.02) and 128,000 for Command R+. Maximum output per response: Pixtral Large (25.02) up to 8,192, Command R+ up to 4,000, Gemini 2.5 Pro Preview 06-05 up to 65,536 tokens.

Which can read images, PDFs, audio or video?

Pixtral Large (25.02) accepts text and images; Command R+ accepts text; Gemini 2.5 Pro Preview 06-05 accepts text, images, PDFs and audio. Gemini 2.5 Pro Preview 06-05 handles the widest range of inputs.

Are any of these open source?

Command R+ publishes its weights and can be self-hosted; Pixtral Large (25.02) and Gemini 2.5 Pro Preview 06-05 is proprietary.

Which is newer?

Gemini 2.5 Pro Preview 06-05 is the newest, released Jun 5, 2025. Pixtral Large (25.02) came out Apr 8, 2025; Command R+ came out Aug 30, 2024. Knowledge cutoff: Command R+ Jun 1, 2024, Gemini 2.5 Pro Preview 06-05 Jan 31, 2025.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Nov 2, 2026.