MiMo-V2-Pro vs Mistral Large 3 vs Qwen3.5 35B-A3B Base
Mistral Large 3 comes out ahead, 52 to 45 and 42 on our weighted score.
XiaomiMiMo-V2-Pro
42/100- ECI—
- Price$1.00 / $3.00
- Context1.05M
- Our pick
Mistral AIMistral Large 3
52/100- ECI—
- Price$0.50 / $1.50
- Context262K
Alibaba (Qwen)Qwen3.5 35B-A3B Base
45/100- ECI—
- Price$0.54 / $1.33
- Context262K
Mistral Large 3 is our pick
Mistral Large 3 is the better all-round choice, scoring 52/100 against Qwen3.5 35B-A3B Base (45) and MiMo-V2-Pro (42). It leads on inputs & features. MiMo-V2-Pro wins on context window. 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 priceQwen3.5 35B-A3B BaseQwen3.5 35B-A3B Base $0.739 · Mistral Large 3 $0.75 · MiMo-V2-Pro $1.50 per 1M tokens (3:1 blend)
- Longest contextMiMo-V2-ProMiMo-V2-Pro 1,048,576 · Mistral Large 3 262,144 · Qwen3.5 35B-A3B Base 262,144 tokens
- Widest inputsQwen3.5 35B-A3B BaseMiMo-V2-Pro: Text · Mistral Large 3: Text, Images · Qwen3.5 35B-A3B Base: Text, Images, Video
- Self-hostingMistral Large 3 and Qwen3.5 35B-A3B BasePublishes downloadable weights (Apache-2.0)
| Measure | Weight | MiMo-V2-Pro | Mistral Large 3 | Qwen3.5 35B-A3B Base |
|---|---|---|---|---|
| Price | 50% | 40 | 53 | 54 |
| Inputs & features | 30% | 35 | 60 | 35 |
| Context window | 20% | 61 | 37 | 37 |
| Overall | 100% | 42/100 | 52/100 | 45/100 |
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 | MiMo-V2-ProXiaomi | Mistral Large 3Mistral AI | Qwen3.5 35B-A3B BaseAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.00 | $0.50 (best) | $0.54 |
| Output | $3.00 | $1.50 | $1.33 (best) |
| Cached input | — | $0.05 | — |
| Blended (3:1) | $1.50 | $0.75 | $0.739 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Mistral API | Median of 1 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 262,144 tokens |
| Max output | 131,072 tokens | 262,144 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | OpenApache-2.0 |
| API model ID | — | mistral-large-2512 | — |
| API providers | 2 | 17 (best) | 1 |
| Released | Mar 18, 2026 | Dec 2, 2025 | Feb 24, 2026 |
| Knowledge cutoff | Dec 2024 | Nov 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- MiMo-V2-Pro$16.00
- Mistral Large 3$8.00
- Qwen3.5 35B-A3B Base$8.07
Which should you choose?
Which is better: MiMo-V2-Pro, Mistral Large 3 or Qwen3.5 35B-A3B Base?
Mistral Large 3 is the better all-round choice, scoring 52/100 against Qwen3.5 35B-A3B Base (45) and MiMo-V2-Pro (42). It leads on inputs & features. MiMo-V2-Pro wins on context window. 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, MiMo-V2-Pro, Mistral Large 3 or Qwen3.5 35B-A3B Base?
Qwen3.5 35B-A3B Base is cheaper at $0.54 input / $1.33 output per million tokens (median across 1 API provider). Mistral Large 3 costs $0.50 input / $1.50 output per million tokens (official Mistral API price); MiMo-V2-Pro costs $1.00 input / $3.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.739 per million tokens for Qwen3.5 35B-A3B Base versus $0.75 for Mistral Large 3 (1× as much) and $1.50 for MiMo-V2-Pro (2× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. MiMo-V2-Pro has not been scored yet, Mistral Large 3 has not been scored yet and Qwen3.5 35B-A3B Base has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for MiMo-V2-Pro, Mistral Large 3 and Qwen3.5 35B-A3B Base yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Qwen3.5 35B-A3B Base does not support tool calling, which most coding agents need.
Which has the bigger context window?
MiMo-V2-Pro has the largest context window at 1,048,576 tokens, against 262,144 for Mistral Large 3 and 262,144 for Qwen3.5 35B-A3B Base. Maximum output per response: MiMo-V2-Pro up to 131,072, Mistral Large 3 up to 262,144, Qwen3.5 35B-A3B Base up to 65,536 tokens.
Which can read images, PDFs, audio or video?
MiMo-V2-Pro accepts text; Mistral Large 3 accepts text and images; Qwen3.5 35B-A3B Base accepts text, images and video. Qwen3.5 35B-A3B Base handles the widest range of inputs.
Are any of these open source?
Mistral Large 3 and Qwen3.5 35B-A3B Base publishes its weights (Apache-2.0) and can be self-hosted; MiMo-V2-Pro is proprietary.
Which is newer?
MiMo-V2-Pro is the newest, released Mar 18, 2026. Qwen3.5 35B-A3B Base came out Feb 24, 2026; Mistral Large 3 came out Dec 2, 2025. Knowledge cutoff: MiMo-V2-Pro Dec 2024, Mistral Large 3 Nov 2024.
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 Nov 2, 2026.
