ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Pixtral Large (25.02) vs MiniMax M1 80K vs Gemini 2.5 Pro Preview 06-05

Too close to call on our weighted score (Gemini 2.5 Pro Preview 06-05 48, MiniMax M1 80K 47, Pixtral Large (25.02) 33). The right pick depends on what you value most.

  1. Mistral AI

    Pixtral Large (25.02)

    Released Apr 8, 2025

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

    MiniMax M1 80K

    Released Jun 17, 2025

    47/100
    • ECI—
    • Price$0.55 / $2.20
    • Context1M
  3. Google

    Gemini 2.5 Pro Preview 06-05

    Released Jun 5, 2025

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

Too close to call

It is close. Our weighted score puts them within 1 points (Gemini 2.5 Pro Preview 06-05 48/100, MiniMax M1 80K 47/100, Pixtral Large (25.02) 33/100), so choose by what matters most for your work: MiniMax M1 80K on price and Gemini 2.5 Pro Preview 06-05 for long inputs. 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 priceMiniMax M1 80KMiniMax M1 80K $0.963 · Pixtral Large (25.02) $3.00 · Gemini 2.5 Pro Preview 06-05 $3.35 per 1M tokens (3:1 blend)
  • Longest contextGemini 2.5 Pro Preview 06-05Gemini 2.5 Pro Preview 06-05 1,048,576 · MiniMax M1 80K 1,000,000 · Pixtral Large (25.02) 128,000 tokens
  • Widest inputsGemini 2.5 Pro Preview 06-05Pixtral Large (25.02): Text, Images · MiniMax M1 80K: Text · Gemini 2.5 Pro Preview 06-05: Text, Images, PDFs, Audio
  • Self-hostingMiniMax M1 80KPublishes downloadable weights (Apache-2.0)
How the score is built
MeasureWeightPixtral Large (25.02)MiniMax M1 80KGemini 2.5 Pro Preview 06-05
Price50%264824
Inputs & features30%503580
Context window20%246061
Overall100%33/10047/10048/100

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 MiniMax M1 80K vs Gemini 2.5 Pro Preview 06-05 specifications side by side
SpecificationPixtral Large (25.02)Mistral AIMiniMax M1 80KMiniMaxGemini 2.5 Pro Preview 06-05Google
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$2.00$0.55 (best)$1.22
Output$6.00$2.20 (best)$9.75
Cached input———
Blended (3:1)$3.00$0.963 (best)$3.35
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 3 providersMedian of 5 providersMedian of 4 providers
Limits
Context window128,000 tokens1,000,000 tokens1,048,576 tokens (best)
Max output8,192 tokens80,000 tokens (best)65,536 tokens
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsNoNoYes
AudioNoNoYes
VideoNoNoNo
ReasoningNoYesYes
Tool callingYesYesYes
Structured outputNoNoNo
Availability
WeightsProprietaryOpenApache-2.0Proprietary
API model ID———
API providers35 (best)4
ReleasedApr 8, 2025Jun 17, 2025Jun 5, 2025
Knowledge cutoff——Jan 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
  • MiniMax M1 80K$9.90
  • Gemini 2.5 Pro Preview 06-05$31.69
04 — Questions

Which should you choose?

Which is better: Pixtral Large (25.02), MiniMax M1 80K or Gemini 2.5 Pro Preview 06-05?

It is close. Our weighted score puts them within 1 points (Gemini 2.5 Pro Preview 06-05 48/100, MiniMax M1 80K 47/100, Pixtral Large (25.02) 33/100), so choose by what matters most for your work: MiniMax M1 80K on price and Gemini 2.5 Pro Preview 06-05 for long inputs. 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), MiniMax M1 80K or Gemini 2.5 Pro Preview 06-05?

MiniMax M1 80K is cheaper at $0.55 input / $2.20 output per million tokens (median across 5 API providers). Pixtral Large (25.02) costs $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). At a typical mix of three input tokens to one output token, that is $0.963 per million tokens for MiniMax M1 80K versus $3.00 for Pixtral Large (25.02) (3.1× as much) and $3.35 for Gemini 2.5 Pro Preview 06-05 (3.5× 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, MiniMax M1 80K 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), MiniMax M1 80K 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 1,000,000 for MiniMax M1 80K and 128,000 for Pixtral Large (25.02). Maximum output per response: Pixtral Large (25.02) up to 8,192, MiniMax M1 80K up to 80,000, 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; MiniMax M1 80K 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?

MiniMax M1 80K publishes its weights (Apache-2.0) and can be self-hosted; Pixtral Large (25.02) and Gemini 2.5 Pro Preview 06-05 is proprietary.

Which is newer?

MiniMax M1 80K is the newest, released Jun 17, 2025. Gemini 2.5 Pro Preview 06-05 came out Jun 5, 2025; Pixtral Large (25.02) came out Apr 8, 2025. Knowledge cutoff: 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.