ZMIME
Comparison · 3 models · Updated Oct 4, 2026

MiniMax-M2.7 vs Qwen3 Max vs GPT-5.4 nano

GPT-5.4 nano comes out ahead, 68 to 61 and 50 on our weighted score, and it is the cheaper option too.

  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. Alibaba (Qwen)

    Qwen3 Max

    Released Sep 23, 2025

    50/100
    • ECI142.4
    • Price$1.20 / $6.00
    • Context262K
    Full specs Remove Qwen3 Max
  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 Qwen3 Max (50). It leads on price, inputs & features and context window. 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 · Qwen3 Max 142.4
  • Lowest priceGPT-5.4 nanoGPT-5.4 nano $0.463 · MiniMax-M2.7 $0.525 · Qwen3 Max $2.40 per 1M tokens (3:1 blend)
  • Longest contextGPT-5.4 nanoGPT-5.4 nano 400,000 · Qwen3 Max 262,144 · MiniMax-M2.7 204,800 tokens
  • Widest inputsGPT-5.4 nanoMiniMax-M2.7: Text · Qwen3 Max: Text · GPT-5.4 nano: Text, Images
  • Self-hostingMiniMax-M2.7Publishes downloadable weights
How the score is built
MeasureWeightMiniMax-M2.7Qwen3 MaxGPT-5.4 nano
CapabilityCapabilities Index (ECI)50%736873
Price25%633266
Inputs & features15%352570
Context window10%323744
Overall100%61/10050/10068/100
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 Qwen3 Max vs GPT-5.4 nano specifications side by side
SpecificationMiniMax-M2.7MiniMaxQwen3 MaxAlibaba (Qwen)GPT-5.4 nanoOpenAI
Capability
Capabilities Index (ECI)145.9 (best)142.4145.8
ECI rank#73 of 148 (best)#91 of 148#75 of 148
GPQA DiamondGraduate-level science questions—72.6%78.5% (best)
FrontierMath Tiers 1–3Research-level mathematics—19.0%44.9% (best)
OTIS Mock AIME 2024–2025Competition mathematics—73.3%87.8% (best)
SimpleQA VerifiedShort factual questions—48.8% (best)11.7%
Price per million tokens
Input$0.30$1.20$0.20 (best)
Output$1.20 (best)$6.00$1.25
Cached input$0.06—$0.02 (best)
Blended (3:1)$0.525$2.40$0.463 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial MiniMax (minimax.io) APIOfficial Alibaba APIOfficial OpenAI API
Limits
Context window204,800 tokens262,144 tokens400,000 tokens (best)
Max output131,072 tokens (best)65,536 tokens128,000 tokens
Inputs and features
TextYesYesYes
ImagesNoNoYes
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoYeslow · medium · high · xhigh
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenProprietaryProprietary
API model IDMiniMax-M2.7qwen3-maxgpt-5.4-nano
API providers29 (best)1626
ReleasedMar 18, 2026Sep 23, 2025Mar 17, 2026
Knowledge cutoff—Apr 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
  • Qwen3 Max$24.00
  • GPT-5.4 nano$4.50
04 — Questions

Which should you choose?

Which is better: MiniMax-M2.7, Qwen3 Max or GPT-5.4 nano?

GPT-5.4 nano is the better all-round choice, scoring 68/100 against MiniMax-M2.7 (61) and Qwen3 Max (50). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, MiniMax-M2.7, Qwen3 Max or GPT-5.4 nano?

GPT-5.4 nano is cheaper at $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); Qwen3 Max costs $1.20 input / $6.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.463 per million tokens for GPT-5.4 nano versus $0.525 for MiniMax-M2.7 (1.1× as much) and $2.40 for Qwen3 Max (5.2× 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 Qwen3 Max 142.4 (#91 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, Qwen3 Max 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 Qwen3 Max and 204,800 for MiniMax-M2.7. Maximum output per response: MiniMax-M2.7 up to 131,072, Qwen3 Max up to 65,536, GPT-5.4 nano up to 128,000 tokens.

Which can read images, PDFs, audio or video?

MiniMax-M2.7 accepts text; Qwen3 Max accepts text; GPT-5.4 nano accepts text and images. GPT-5.4 nano handles the widest range of inputs.

Are any of these open source?

MiniMax-M2.7 publishes its weights and can be self-hosted; Qwen3 Max and 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; Qwen3 Max came out Sep 23, 2025. Knowledge cutoff: Qwen3 Max Apr 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

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