ZMIME
Comparison · 3 models · Updated Oct 4, 2026

MiniMax-M2.7 vs Qwen3.5 Plus vs GPT-5.4 nano

Too close to call on our weighted score (GPT-5.4 nano 68, Qwen3.5 Plus 66, 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. Alibaba (Qwen)

    Qwen3.5 Plus

    Released Feb 16, 2026

    66/100
    • ECI146.8
    • Price$0.40 / $2.40
    • Context1M
    Full specs Remove Qwen3.5 Plus

  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 1 points (GPT-5.4 nano 68/100, Qwen3.5 Plus 66/100, MiniMax-M2.7 61/100), so choose by what matters most for your work: Qwen3.5 Plus for raw capability and GPT-5.4 nano on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityQwen3.5 PlusCapabilities Index (ECI): Qwen3.5 Plus 146.8 · MiniMax-M2.7 145.9 · GPT-5.4 nano 145.8
  • Lowest priceGPT-5.4 nanoGPT-5.4 nano $0.463 · MiniMax-M2.7 $0.525 · Qwen3.5 Plus $0.90 per 1M tokens (3:1 blend)
  • Longest contextQwen3.5 PlusQwen3.5 Plus 1,000,000 · GPT-5.4 nano 400,000 · MiniMax-M2.7 204,800 tokens
  • Widest inputsQwen3.5 PlusMiniMax-M2.7: Text · Qwen3.5 Plus: Text, Images, Video · GPT-5.4 nano: Text, Images
  • Self-hostingMiniMax-M2.7Publishes downloadable weights
How the score is built
MeasureWeightMiniMax-M2.7Qwen3.5 PlusGPT-5.4 nano
CapabilityCapabilities Index (ECI)50%737473
Price25%635266
Inputs & features15%357070
Context window10%326044
Overall100%61/10066/10068/100
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 Qwen3.5 Plus vs GPT-5.4 nano specifications side by side
SpecificationMiniMax-M2.7MiniMaxQwen3.5 PlusAlibaba (Qwen)GPT-5.4 nanoOpenAI
Capability
Capabilities Index (ECI)145.9146.8 (best)145.8
ECI rank#73 of 148#65 of 148 (best)#75 of 148
GPQA DiamondGraduate-level science questions—84.9% (best)78.5%
FrontierMath Tiers 1–3Research-level mathematics——44.9%
OTIS Mock AIME 2024–2025Competition mathematics—86.7%87.8% (best)
SimpleQA VerifiedShort factual questions—25.4% (best)11.7%
Price per million tokens
Input$0.30$0.40$0.20 (best)
Output$1.20 (best)$2.40$1.25
Cached input$0.06—$0.02 (best)
Blended (3:1)$0.525$0.90$0.463 (best)
Long-context rateSame rateSame rateSame rate
Price sourceOfficial MiniMax (minimax.io) APIOfficial Alibaba APIOfficial OpenAI API
Limits
Context window204,800 tokens1,000,000 tokens (best)400,000 tokens
Max output131,072 tokens (best)65,536 tokens128,000 tokens
Inputs and features
TextYesYesYes
ImagesNoYesYes
PDFsNoNoNo
AudioNoNoNo
VideoNoYesNo
ReasoningYesYesYeslow · medium · high · xhigh
Tool callingYesYesYes
Structured outputNoNoYes
Availability
WeightsOpenProprietaryProprietary
API model IDMiniMax-M2.7qwen3.5-plusgpt-5.4-nano
API providers29 (best)1026
ReleasedMar 18, 2026Feb 16, 2026Mar 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
  • Qwen3.5 Plus$8.80
  • GPT-5.4 nano$4.50
04 — Questions

Which should you choose?

Which is better: MiniMax-M2.7, Qwen3.5 Plus or GPT-5.4 nano?

It is close. Our weighted score puts them within 1 points (GPT-5.4 nano 68/100, Qwen3.5 Plus 66/100, MiniMax-M2.7 61/100), so choose by what matters most for your work: Qwen3.5 Plus for raw capability and GPT-5.4 nano on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, MiniMax-M2.7, Qwen3.5 Plus 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); Qwen3.5 Plus costs $0.40 input / $2.40 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 $0.90 for Qwen3.5 Plus (1.9× as much).

Which scores higher on benchmarks?

Qwen3.5 Plus scores higher on the Capabilities Index (ECI): Qwen3.5 Plus 146.8 (#65 of 148), MiniMax-M2.7 145.9 (#73 of 148) and GPT-5.4 nano 145.8 (#75 of 148). The confidence ranges of the top two overlap (144.6–148.1 vs 138.2–148.0), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for MiniMax-M2.7, Qwen3.5 Plus and GPT-5.4 nano yet, so there is no like-for-like coding score. On overall capability, Qwen3.5 Plus 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?

Qwen3.5 Plus has the largest context window at 1,000,000 tokens, against 400,000 for GPT-5.4 nano and 204,800 for MiniMax-M2.7. Maximum output per response: MiniMax-M2.7 up to 131,072, Qwen3.5 Plus 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; Qwen3.5 Plus accepts text, images and video; GPT-5.4 nano accepts text and images. Qwen3.5 Plus handles the widest range of inputs.

Are any of these open source?

MiniMax-M2.7 publishes its weights and can be self-hosted; Qwen3.5 Plus 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; Qwen3.5 Plus came out Feb 16, 2026. Knowledge cutoff: Qwen3.5 Plus 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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