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Comparison · 3 models · Updated Oct 4, 2026

MiniMax-M2.7 vs Gemma 4 31B IT vs GPT-5.4 nano

Too close to call on our weighted score (Gemma 4 31B IT 69, GPT-5.4 nano 68, MiniMax-M2.7 61). The right pick depends on what you value most.

  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. Google

    Gemma 4 31B IT

    Released Apr 2, 2026

    69/100
    • ECI142.8
    • Price$0.14 / $0.40
    • Context262K
    Full specs Remove Gemma 4 31B IT

  3. 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

Too close to call

It is close. Our weighted score puts them within 2 points (Gemma 4 31B IT 69/100, GPT-5.4 nano 68/100, MiniMax-M2.7 61/100), so choose by what matters most for your work: MiniMax-M2.7 for raw capability, Gemma 4 31B IT on price and GPT-5.4 nano for long inputs. 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 · Gemma 4 31B IT 142.8
  • Lowest priceGemma 4 31B ITGemma 4 31B IT $0.205 · 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 · Gemma 4 31B IT 262,144 · MiniMax-M2.7 204,800 tokens
  • Widest inputsGemma 4 31B IT and GPT-5.4 nanoMiniMax-M2.7: Text · Gemma 4 31B IT: Text, Images · GPT-5.4 nano: Text, Images
  • Self-hostingMiniMax-M2.7 and Gemma 4 31B ITPublishes downloadable weights
How the score is built
MeasureWeightMiniMax-M2.7Gemma 4 31B ITGPT-5.4 nano
CapabilityCapabilities Index (ECI)50%736973
Price25%638366
Inputs & features15%357070
Context window10%323744
Overall100%61/10069/10068/100
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 Gemma 4 31B IT vs GPT-5.4 nano specifications side by side
SpecificationMiniMax-M2.7MiniMaxGemma 4 31B ITGoogleGPT-5.4 nanoOpenAI
Capability
Capabilities Index (ECI)145.9 (best)142.8145.8
ECI rank#73 of 148 (best)#86 of 148#75 of 148
GPQA DiamondGraduate-level science questions—75.8%78.5% (best)
FrontierMath Tiers 1–3Research-level mathematics——44.9%
OTIS Mock AIME 2024–2025Competition mathematics—73.3%87.8% (best)
SimpleQA VerifiedShort factual questions—10.4%11.7% (best)
Price per million tokens
Input$0.30$0.14 (best)$0.20
Output$1.20$0.40 (best)$1.25
Cached input$0.06—$0.02 (best)
Blended (3:1)$0.525$0.205 (best)$0.463
Long-context rateSame rateSame rateSame rate
Price sourceOfficial MiniMax (minimax.io) APIMedian of 30 providersOfficial OpenAI API
Limits
Context window204,800 tokens262,144 tokens400,000 tokens (best)
Max output131,072 tokens (best)32,768 tokens128,000 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesYesYeslow · medium · high · xhigh
Tool callingYesYesYes
Structured outputNoYesYes
Availability
WeightsOpenOpenProprietary
API model IDMiniMax-M2.7gemma-4-31b-itgpt-5.4-nano
API providers2938 (best)26
ReleasedMar 18, 2026Apr 2, 2026Mar 17, 2026
Knowledge cutoff——Aug 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
  • Gemma 4 31B IT$2.20
  • GPT-5.4 nano$4.50
04 — Questions

Which should you choose?

Which is better: MiniMax-M2.7, Gemma 4 31B IT or GPT-5.4 nano?

It is close. Our weighted score puts them within 2 points (Gemma 4 31B IT 69/100, GPT-5.4 nano 68/100, MiniMax-M2.7 61/100), so choose by what matters most for your work: MiniMax-M2.7 for raw capability, Gemma 4 31B IT on price and GPT-5.4 nano for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, MiniMax-M2.7, Gemma 4 31B IT or GPT-5.4 nano?

Gemma 4 31B IT is cheaper at $0.14 input / $0.40 output per million tokens (median across 30 API providers). 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 $0.205 per million tokens for Gemma 4 31B IT versus $0.463 for GPT-5.4 nano (2.3× as much) and $0.525 for MiniMax-M2.7 (2.6× 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 Gemma 4 31B IT 142.8 (#86 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, Gemma 4 31B IT 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 262,144 for Gemma 4 31B IT and 204,800 for MiniMax-M2.7. Maximum output per response: MiniMax-M2.7 up to 131,072, Gemma 4 31B IT up to 32,768, GPT-5.4 nano up to 128,000 tokens.

Which can read images, PDFs, audio or video?

MiniMax-M2.7 accepts text; Gemma 4 31B IT accepts text and images; GPT-5.4 nano accepts text and images. Gemma 4 31B IT handles the widest range of inputs.

Are any of these open source?

MiniMax-M2.7 and Gemma 4 31B IT publishes its weights and can be self-hosted; GPT-5.4 nano is proprietary.

Which is newer?

Gemma 4 31B IT is the newest, released Apr 2, 2026. MiniMax-M2.7 came out Mar 18, 2026; GPT-5.4 nano came out Mar 17, 2026. Knowledge cutoff: 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

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