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Comparison · 2 models · Updated Oct 4, 2026

MiniMax-M3 vs GPT-5.4 nano

Too close to call on our weighted score (MiniMax-M3 69, GPT-5.4 nano 68). The right pick depends on what you value most.

  1. MiniMax

    MiniMax-M3

    Released Jun 1, 2026

    69/100
    • ECI147.0
    • Price$0.30 / $1.20
    • Context1.05M
  2. OpenAI

    GPT-5.4 nano

    Released Mar 17, 2026

    68/100
    • ECI145.8
    • Price$0.20 / $1.25
    • Context400K
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01 — Verdict

Too close to call

It is close. Our weighted score puts them within 2 points (MiniMax-M3 69/100, GPT-5.4 nano 68/100), so choose by what matters most for your work: MiniMax-M3 for raw capability and GPT-5.4 nano on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityMiniMax-M3Capabilities Index (ECI): MiniMax-M3 147.0 · GPT-5.4 nano 145.8
  • Lowest priceGPT-5.4 nanoGPT-5.4 nano $0.463 · MiniMax-M3 $0.525 per 1M tokens (3:1 blend)
  • Longest contextMiniMax-M3MiniMax-M3 1,048,576 · GPT-5.4 nano 400,000 tokens
  • Widest inputsMiniMax-M3MiniMax-M3: Text, Images, Video · GPT-5.4 nano: Text, Images
  • Self-hostingMiniMax-M3Publishes downloadable weights
How the score is built
MeasureWeightMiniMax-M3GPT-5.4 nano
CapabilityCapabilities Index (ECI)50%7473
Price25%6366
Inputs & features15%7070
Context window10%6144
Overall100%69/10068/100
02 — Side by side

Every spec in one table

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

MiniMax-M3 vs GPT-5.4 nano specifications side by side
SpecificationMiniMax-M3MiniMaxGPT-5.4 nanoOpenAI
Capability
Capabilities Index (ECI)147.0 (best)145.8
ECI rank#62 of 148 (best)#75 of 148
GPQA DiamondGraduate-level science questions90.9% (best)78.5%
FrontierMath Tiers 1–3Research-level mathematics—44.9%
OTIS Mock AIME 2024–2025Competition mathematics71.1%87.8% (best)
SimpleQA VerifiedShort factual questions—11.7%
Price per million tokens
Input$0.30$0.20 (best)
Output$1.20 (best)$1.25
Cached input$0.06$0.02 (best)
Blended (3:1)$0.525$0.463 (best)
Long-context rateOver 512K: $0.60 / $2.40Same rate
Price sourceOfficial MiniMax (minimax.io) APIOfficial OpenAI API
Limits
Context window1,048,576 tokens (best)400,000 tokens
Max output512,000 tokens (best)128,000 tokens
Inputs and features
TextYesYes
ImagesYesYes
PDFsNoNo
AudioNoNo
VideoYesNo
ReasoningYesYeslow · medium · high · xhigh
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenProprietary
API model IDMiniMax-M3gpt-5.4-nano
API providers42 (best)26
ReleasedJun 1, 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-M3$5.40
  • GPT-5.4 nano$4.50
04 — Questions

Which should you choose?

Which is better: MiniMax-M3 or GPT-5.4 nano?

It is close. Our weighted score puts them within 2 points (MiniMax-M3 69/100, GPT-5.4 nano 68/100), so choose by what matters most for your work: MiniMax-M3 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-M3 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-M3 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 $0.463 per million tokens for GPT-5.4 nano versus $0.525 for MiniMax-M3 (1.1× as much).

Which scores higher on benchmarks?

MiniMax-M3 scores higher on the Capabilities Index (ECI): MiniMax-M3 147.0 (#62 of 148) and GPT-5.4 nano 145.8 (#75 of 148). The confidence ranges of the top two overlap (142.7–149.8 vs 143.2–147.7), so treat the gap as small. On individual benchmarks: GPQA Diamond — MiniMax-M3 90.9%, GPT-5.4 nano 78.5%; OTIS Mock AIME 2024–2025 — GPT-5.4 nano 87.8%, MiniMax-M3 71.1%.

Which is better for coding?

There are no published SWE-bench Verified results for MiniMax-M3 and GPT-5.4 nano yet, so there is no like-for-like coding score. On overall capability, MiniMax-M3 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

MiniMax-M3 has the largest context window at 1,048,576 tokens, against 400,000 for GPT-5.4 nano. Maximum output per response: MiniMax-M3 up to 512,000, GPT-5.4 nano up to 128,000 tokens.

Which can read images, PDFs, audio or video?

MiniMax-M3 accepts text, images and video; GPT-5.4 nano accepts text and images. MiniMax-M3 handles the widest range of inputs.

Are any of these open source?

MiniMax-M3 publishes its weights and can be self-hosted; GPT-5.4 nano is proprietary.

Which is newer?

MiniMax-M3 is the newest, released Jun 1, 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.