MiniMax-M2 vs Mistral Large 3 vs Qwen3-VL Plus
Qwen3-VL Plus comes out ahead, 56 to 50 and 48 on our weighted score.
MiniMax
MiniMax-M2
48/100- ECI—
- Price$0.30 / $1.20
- Context205K
Mistral AI
Mistral Large 3
50/100- ECI—
- Price$0.50 / $1.50
- Context262K
- Our pick
Alibaba (Qwen)
Qwen3-VL Plus
56/100- ECI—
- Price$0.20 / $1.60
- Context262K
Qwen3-VL Plus is our pick
Qwen3-VL Plus is the better all-round choice, scoring 56/100 against Mistral Large 3 (50) and MiniMax-M2 (48). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceMiniMax-M2MiniMax-M2 $0.525 · Qwen3-VL Plus $0.55 · Mistral Large 3 $0.75 per 1M tokens (3:1 blend)
- Longest contextMistral Large 3 and Qwen3-VL PlusMistral Large 3 262,144 · Qwen3-VL Plus 262,144 · MiniMax-M2 204,800 tokens
- Widest inputsMistral Large 3 and Qwen3-VL PlusMiniMax-M2: Text · Mistral Large 3: Text, Images · Qwen3-VL Plus: Text, Images
- Self-hostingMiniMax-M2 and Mistral Large 3Publishes downloadable weights
| Measure | Weight | MiniMax-M2 | Mistral Large 3 | Qwen3-VL Plus |
|---|---|---|---|---|
| Price | 50% | 63 | 56 | 62 |
| Inputs & features | 30% | 35 | 50 | 60 |
| Context window | 20% | 32 | 37 | 37 |
| Overall | 100% | 48/100 | 50/100 | 56/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.30 | $0.50 | $0.20 (best) |
| Output | $1.20 (best) | $1.50 | $1.60 |
| Cached input | — | $0.05 | — |
| Blended (3:1) | $0.525 (best) | $0.75 | $0.55 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official MiniMax (minimax.io) API | Official Mistral API | Official Alibaba API |
| Limits | |||
| Context window | 204,800 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 131,072 tokens | 262,144 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | MiniMax-M2 | mistral-large-2512 | qwen3-vl-plus |
| API providers | 13 (best) | 13 (best) | 6 |
| Released | Oct 27, 2025 | Dec 2, 2025 | Sep 23, 2025 |
| Knowledge cutoff | — | Nov 2024 | 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.
MiniMax-M2$5.40
Mistral Large 3$8.00
Qwen3-VL Plus$5.20
Which should you choose?
Which is better: MiniMax-M2, Mistral Large 3 or Qwen3-VL Plus?
Qwen3-VL Plus is the better all-round choice, scoring 56/100 against Mistral Large 3 (50) and MiniMax-M2 (48). It leads on inputs & features. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, MiniMax-M2, Mistral Large 3 or Qwen3-VL Plus?
MiniMax-M2 is cheaper at $0.30 input / $1.20 output per million tokens (official MiniMax (minimax.io) API price). Qwen3-VL Plus costs $0.20 input / $1.60 output per million tokens (official Alibaba API price); Mistral Large 3 costs $0.50 input / $1.50 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for MiniMax-M2 versus $0.55 for Qwen3-VL Plus (1× as much) and $0.75 for Mistral Large 3 (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiniMax-M2 has not been scored yet, Mistral Large 3 has not been scored yet and Qwen3-VL Plus has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiniMax-M2, Mistral Large 3 and Qwen3-VL Plus yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Mistral Large 3 and Qwen3-VL Plus have the largest context windows (262,144 and 262,144 tokens), against 204,800 for MiniMax-M2. Maximum output per response: MiniMax-M2 up to 131,072, Mistral Large 3 up to 262,144, Qwen3-VL Plus up to 32,768 tokens.
Which can read images, PDFs, audio or video?
MiniMax-M2 accepts text; Mistral Large 3 accepts text and images; Qwen3-VL Plus accepts text and images. Mistral Large 3 handles the widest range of inputs.
Are any of these open source?
MiniMax-M2 and Mistral Large 3 publishes its weights and can be self-hosted; Qwen3-VL Plus is proprietary.
Which is newer?
Mistral Large 3 is the newest, released Dec 2, 2025. MiniMax-M2 came out Oct 27, 2025; Qwen3-VL Plus came out Sep 23, 2025. Knowledge cutoff: Mistral Large 3 Nov 2024, Qwen3-VL Plus 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.