ZMIME
Comparison · 3 models · Updated Oct 4, 2026

MiniMax-M2.7 vs Mistral Small 3.2 vs GPT-5.4 nano

GPT-5.4 nano comes out ahead, 68 to 61 and 60 on our weighted score, though Mistral Small 3.2 is 3.1× cheaper per token.

  1. MiniMax

    MiniMax-M2.7

    Released Mar 18, 2026

    61/100
    • ECI145.9
    • Price$0.30 / $1.20
    • Context205K
    Full specs Remove MiniMax-M2.7

  2. Mistral AI

    Mistral Small 3.2

    Released Jun 20, 2025

    60/100
    • ECI131.7
    • Price$0.10 / $0.30
    • Context128K
    Full specs Remove Mistral Small 3.2
  3. Our pick

    OpenAI

    GPT-5.4 nano

    Released Mar 17, 2026

    68/100
    • ECI145.8
    • Price$0.20 / $1.25
    • Context400K
    Full specs Remove GPT-5.4 nano
01 — Verdict

GPT-5.4 nano is our pick

GPT-5.4 nano is the better all-round choice, scoring 68/100 against MiniMax-M2.7 (61) and Mistral Small 3.2 (60). It leads on inputs & features and context window. Mistral Small 3.2 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMiniMax-M2.7Capabilities Index (ECI): MiniMax-M2.7 145.9 · GPT-5.4 nano 145.8 · Mistral Small 3.2 131.7
  • Lowest priceMistral Small 3.2Mistral Small 3.2 $0.15 · GPT-5.4 nano $0.463 · MiniMax-M2.7 $0.525 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.4 nanoGPT-5.4 nano 400,000 · MiniMax-M2.7 204,800 · Mistral Small 3.2 128,000 tokens
  • Widest inputsMistral Small 3.2 and GPT-5.4 nanoMiniMax-M2.7: Text · Mistral Small 3.2: Text, Images · GPT-5.4 nano: Text, Images
  • Self-hostingMiniMax-M2.7 and Mistral Small 3.2Publishes downloadable weights
How the score is built
MeasureWeightMiniMax-M2.7Mistral Small 3.2GPT-5.4 nano
CapabilityCapabilities Index (ECI)50%735573
Price25%638966
Inputs & features15%355070
Context window10%322444
Overall100%61/10060/10068/100
02 — Side by side

Every spec in one table

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

MiniMax-M2.7 vs Mistral Small 3.2 vs GPT-5.4 nano specifications side by side
SpecificationMiniMax-M2.7MiniMaxMistral Small 3.2Mistral AIGPT-5.4 nanoOpenAI
Capability
Capabilities Index (ECI)145.9 (best)131.7145.8
ECI rank#73 of 148 (best)#123 of 148#75 of 148
GPQA DiamondGraduate-level science questions—49.1%78.5% (best)
FrontierMath Tiers 1–3Research-level mathematics——44.9%
OTIS Mock AIME 2024–2025Competition mathematics—30.3%87.8% (best)
SimpleQA VerifiedShort factual questions——11.7%
Price per million tokens
Input$0.30$0.10 (best)$0.20
Output$1.20$0.30 (best)$1.25
Cached input$0.06—$0.02 (best)
Blended (3:1)$0.525$0.15 (best)$0.463
Long-context rateSame rateSame rateSame rate
Price sourceOfficial MiniMax (minimax.io) APIOfficial Mistral APIOfficial OpenAI API
Limits
Context window204,800 tokens128,000 tokens400,000 tokens (best)
Max output131,072 tokens (best)16,384 tokens128,000 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoYeslow · medium · high · xhigh
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenOpenProprietary
API model IDMiniMax-M2.7mistral-small-2506gpt-5.4-nano
API providers29 (best)626
ReleasedMar 18, 2026Jun 20, 2025Mar 17, 2026
Knowledge cutoff—Mar 2025Aug 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.

  • MiniMax-M2.7$5.40
  • Mistral Small 3.2$1.60
  • GPT-5.4 nano$4.50
04 — Questions

Which should you choose?

Which is better: MiniMax-M2.7, Mistral Small 3.2 or GPT-5.4 nano?

GPT-5.4 nano is the better all-round choice, scoring 68/100 against MiniMax-M2.7 (61) and Mistral Small 3.2 (60). It leads on inputs & features and context window. Mistral Small 3.2 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, MiniMax-M2.7, Mistral Small 3.2 or GPT-5.4 nano?

Mistral Small 3.2 is cheaper at $0.10 input / $0.30 output per million tokens (official Mistral API price). GPT-5.4 nano costs $0.20 input / $1.25 output per million tokens (official OpenAI API price); MiniMax-M2.7 costs $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Mistral Small 3.2 versus $0.463 for GPT-5.4 nano (3.1× as much) and $0.525 for MiniMax-M2.7 (3.5× as much).

Which scores higher on benchmarks?

MiniMax-M2.7 scores higher on the Capabilities Index (ECI): MiniMax-M2.7 145.9 (#73 of 148), GPT-5.4 nano 145.8 (#75 of 148) and Mistral Small 3.2 131.7 (#123 of 148). The confidence ranges of the top two overlap (138.2–148.0 vs 143.2–147.7), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for MiniMax-M2.7, Mistral Small 3.2 and GPT-5.4 nano yet, so there is no like-for-like coding score. On overall capability, MiniMax-M2.7 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

GPT-5.4 nano has the largest context window at 400,000 tokens, against 204,800 for MiniMax-M2.7 and 128,000 for Mistral Small 3.2. Maximum output per response: MiniMax-M2.7 up to 131,072, Mistral Small 3.2 up to 16,384, GPT-5.4 nano up to 128,000 tokens.

Which can read images, PDFs, audio or video?

MiniMax-M2.7 accepts text; Mistral Small 3.2 accepts text and images; GPT-5.4 nano accepts text and images. Mistral Small 3.2 handles the widest range of inputs.

Are any of these open source?

MiniMax-M2.7 and Mistral Small 3.2 publishes its weights and can be self-hosted; GPT-5.4 nano is proprietary.

Which is newer?

MiniMax-M2.7 is the newest, released Mar 18, 2026. GPT-5.4 nano came out Mar 17, 2026; Mistral Small 3.2 came out Jun 20, 2025. Knowledge cutoff: Mistral Small 3.2 Mar 2025, GPT-5.4 nano Aug 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 Oct 4, 2026.

05 — Keep comparing

Related comparisons