GPT-5.4 nano vs MiniMax-M2.5 vs Qwen3 Max
GPT-5.4 nano comes out ahead, 68 to 61 and 50 on our weighted score, and it is the cheaper option too.
- Our pick
OpenAI
GPT-5.4 nano
68/100- ECI145.8
- Price$0.20 / $1.25
- Context400K
MiniMax
MiniMax-M2.5
61/100- ECI146.7
- Price$0.30 / $1.20
- Context205K
Alibaba (Qwen)
Qwen3 Max
50/100- ECI142.4
- Price$1.20 / $6.00
- Context262K
GPT-5.4 nano is our pick
GPT-5.4 nano is the better all-round choice, scoring 68/100 against MiniMax-M2.5 (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-M2.5Capabilities Index (ECI): MiniMax-M2.5 146.7 · GPT-5.4 nano 145.8 · Qwen3 Max 142.4
- Lowest priceGPT-5.4 nanoGPT-5.4 nano $0.463 · MiniMax-M2.5 $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-M2.5 204,800 tokens
- Widest inputsGPT-5.4 nanoGPT-5.4 nano: Text, Images · MiniMax-M2.5: Text · Qwen3 Max: Text
- Self-hostingMiniMax-M2.5Publishes downloadable weights
| Measure | Weight | GPT-5.4 nano | MiniMax-M2.5 | Qwen3 Max |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 73 | 74 | 68 |
| Price | 25% | 66 | 63 | 32 |
| Inputs & features | 15% | 70 | 35 | 25 |
| Context window | 10% | 44 | 32 | 37 |
| Overall | 100% | 68/100 | 61/100 | 50/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 145.8 | 146.7 (best) | 142.4 |
| ECI rank | #75 of 148 | #66 of 148 (best) | #91 of 148 |
| GPQA DiamondGraduate-level science questions | 78.5% (best) | — | 72.6% |
| FrontierMath Tiers 1–3Research-level mathematics | 44.9% (best) | — | 19.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 87.8% (best) | — | 73.3% |
| SimpleQA VerifiedShort factual questions | 11.7% | — | 48.8% (best) |
| Price per million tokens | |||
| Input | $0.20 (best) | $0.30 | $1.20 |
| Output | $1.25 | $1.20 (best) | $6.00 |
| Cached input | $0.02 (best) | $0.03 | — |
| Blended (3:1) | $0.463 (best) | $0.525 | $2.40 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official OpenAI API | Official MiniMax (minimax.io) API | Official Alibaba API |
| Limits | |||
| Context window | 400,000 tokens (best) | 204,800 tokens | 262,144 tokens |
| Max output | 128,000 tokens | 131,072 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yeslow · medium · high · xhigh | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gpt-5.4-nano | MiniMax-M2.5 | qwen3-max |
| API providers | 26 (best) | 21 | 16 |
| Released | Mar 17, 2026 | Feb 12, 2026 | Sep 23, 2025 |
| Knowledge cutoff | Aug 31, 2025 | — | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
GPT-5.4 nano$4.50
MiniMax-M2.5$5.40
Qwen3 Max$24.00
Which should you choose?
Which is better: GPT-5.4 nano, MiniMax-M2.5 or Qwen3 Max?
GPT-5.4 nano is the better all-round choice, scoring 68/100 against MiniMax-M2.5 (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, GPT-5.4 nano, MiniMax-M2.5 or Qwen3 Max?
GPT-5.4 nano is cheaper at $0.20 input / $1.25 output per million tokens (official OpenAI API price). MiniMax-M2.5 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-M2.5 (1.1× as much) and $2.40 for Qwen3 Max (5.2× as much).
Which scores higher on benchmarks?
MiniMax-M2.5 scores higher on the Capabilities Index (ECI): MiniMax-M2.5 146.7 (#66 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 (142.3–147.9 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 GPT-5.4 nano, MiniMax-M2.5 and Qwen3 Max yet, so there is no like-for-like coding score. On overall capability, MiniMax-M2.5 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-M2.5. Maximum output per response: GPT-5.4 nano up to 128,000, MiniMax-M2.5 up to 131,072, Qwen3 Max up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GPT-5.4 nano accepts text and images; MiniMax-M2.5 accepts text; Qwen3 Max accepts text. GPT-5.4 nano handles the widest range of inputs.
Are any of these open source?
MiniMax-M2.5 publishes its weights and can be self-hosted; GPT-5.4 nano and Qwen3 Max is proprietary.
Which is newer?
GPT-5.4 nano is the newest, released Mar 17, 2026. MiniMax-M2.5 came out Feb 12, 2026; Qwen3 Max came out Sep 23, 2025. Knowledge cutoff: GPT-5.4 nano Aug 31, 2025, Qwen3 Max Apr 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.