Qwen3.5 122B-A10B vs Mistral Large 3 vs Grok Build 0.1
Too close to call on our weighted score (Qwen3.5 122B-A10B 54, Grok Build 0.1 53, Mistral Large 3 52). The right pick depends on what you value most.
Alibaba (Qwen)Qwen3.5 122B-A10B
54/100- ECI—
- Price$0.40 / $3.20
- Context262K
Mistral AIMistral Large 3
52/100- ECI—
- Price$0.50 / $1.50
- Context262K
xAIGrok Build 0.1
53/100- ECI—
- Price$1.00 / $2.00
- Context256K
Too close to call
It is close. Our weighted score puts them within 1 points (Qwen3.5 122B-A10B 54/100, Grok Build 0.1 53/100, Mistral Large 3 52/100), so choose by what matters most for your work: Mistral Large 3 on price. 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 priceMistral Large 3Mistral Large 3 $0.75 · Qwen3.5 122B-A10B $1.10 · Grok Build 0.1 $1.25 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 122B-A10B and Mistral Large 3Qwen3.5 122B-A10B 262,144 · Mistral Large 3 262,144 · Grok Build 0.1 256,000 tokens
- Widest inputsQwen3.5 122B-A10B and Grok Build 0.1Qwen3.5 122B-A10B: Text, Images, Video · Mistral Large 3: Text, Images · Grok Build 0.1: Text, Images, PDFs
- Self-hostingQwen3.5 122B-A10B and Mistral Large 3Publishes downloadable weights
| Measure | Weight | Qwen3.5 122B-A10B | Mistral Large 3 | Grok Build 0.1 |
|---|---|---|---|---|
| Price | 50% | 46 | 53 | 43 |
| Inputs & features | 30% | 80 | 60 | 80 |
| Context window | 20% | 37 | 37 | 36 |
| Overall | 100% | 54/100 | 52/100 | 53/100 |
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 | Qwen3.5 122B-A10BAlibaba (Qwen) | Mistral Large 3Mistral AI | Grok Build 0.1xAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.40 (best) | $0.50 | $1.00 |
| Output | $3.20 | $1.50 (best) | $2.00 |
| Cached input | — | $0.05 (best) | $0.20 |
| Blended (3:1) | $1.10 | $0.75 (best) | $1.25 |
| Long-context rate | Same rate | Same rate | Over 200K: $2.00 / $4.00 |
| Price source | Official Alibaba API | Official Mistral API | Official xAI API |
| Limits | |||
| Context window | 262,144 tokens (best) | 262,144 tokens (best) | 256,000 tokens |
| Max output | 65,536 tokens | 262,144 tokens (best) | 256,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Open | Proprietary |
| API model ID | qwen3.5-122b-a10b | mistral-large-2512 | grok-build-0.1 |
| API providers | 22 (best) | 17 | 20 |
| Released | Feb 23, 2026 | Dec 2, 2025 | Apr 16, 2026 |
| Knowledge cutoff | — | 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.
- Qwen3.5 122B-A10B$10.40
- Mistral Large 3$8.00
- Grok Build 0.1$14.00
Which should you choose?
Which is better: Qwen3.5 122B-A10B, Mistral Large 3 or Grok Build 0.1?
It is close. Our weighted score puts them within 1 points (Qwen3.5 122B-A10B 54/100, Grok Build 0.1 53/100, Mistral Large 3 52/100), so choose by what matters most for your work: Mistral Large 3 on price. 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, Qwen3.5 122B-A10B, Mistral Large 3 or Grok Build 0.1?
Mistral Large 3 is cheaper at $0.50 input / $1.50 output per million tokens (official Mistral API price). Qwen3.5 122B-A10B costs $0.40 input / $3.20 output per million tokens (official Alibaba API price); Grok Build 0.1 costs $1.00 input / $2.00 output per million tokens (official xAI API price). At a typical mix of three input tokens to one output token, that is $0.75 per million tokens for Mistral Large 3 versus $1.10 for Qwen3.5 122B-A10B (1.5× as much) and $1.25 for Grok Build 0.1 (1.7× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.5 122B-A10B has not been scored yet, Mistral Large 3 has not been scored yet and Grok Build 0.1 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.5 122B-A10B, Mistral Large 3 and Grok Build 0.1 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?
Qwen3.5 122B-A10B and Mistral Large 3 have the largest context windows (262,144 and 262,144 tokens), against 256,000 for Grok Build 0.1. Maximum output per response: Qwen3.5 122B-A10B up to 65,536, Mistral Large 3 up to 262,144, Grok Build 0.1 up to 256,000 tokens.
Which can read images, PDFs, audio or video?
Qwen3.5 122B-A10B accepts text, images and video; Mistral Large 3 accepts text and images; Grok Build 0.1 accepts text, images and PDFs. Qwen3.5 122B-A10B handles the widest range of inputs.
Are any of these open source?
Qwen3.5 122B-A10B and Mistral Large 3 publishes its weights and can be self-hosted; Grok Build 0.1 is proprietary.
Which is newer?
Grok Build 0.1 is the newest, released Apr 16, 2026. Qwen3.5 122B-A10B came out Feb 23, 2026; Mistral Large 3 came out Dec 2, 2025. Knowledge cutoff: 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.
