Magistral Medium vs QVQ Max vs Qwen3-Coder 480B-A35B Instruct
QVQ Max comes out ahead, 40 to 30 and 28 on our weighted score, and it is the cheaper option too.
Mistral AIMagistral Medium
30/100- ECI—
- Price$2.00 / $5.00
- Context128K
- Our pick
Alibaba (Qwen)QVQ Max
40/100- ECI—
- Price$1.20 / $4.80
- Context131K
- Alibaba (Qwen)
Qwen3-Coder 480B-A35B Instruct
28/100- ECI—
- Price$1.50 / $7.50
- Context262K
QVQ Max is our pick
QVQ Max is the better all-round choice, scoring 40/100 against Magistral Medium (30) and Qwen3-Coder 480B-A35B Instruct (28). It leads on price and inputs & features. Qwen3-Coder 480B-A35B Instruct 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 priceQVQ MaxQVQ Max $2.10 · Magistral Medium $2.75 · Qwen3-Coder 480B-A35B Instruct $3.00 per 1M tokens (3:1 blend)
- Longest contextQwen3-Coder 480B-A35B InstructQwen3-Coder 480B-A35B Instruct 262,144 · QVQ Max 131,072 · Magistral Medium 128,000 tokens
- Widest inputsQVQ MaxMagistral Medium: Text · QVQ Max: Text, Images · Qwen3-Coder 480B-A35B Instruct: Text
- Self-hostingQwen3-Coder 480B-A35B InstructPublishes downloadable weights
| Measure | Weight | Magistral Medium | QVQ Max | Qwen3-Coder 480B-A35B Instruct |
|---|---|---|---|---|
| Price | 50% | 29 | 35 | 27 |
| Inputs & features | 30% | 35 | 60 | 25 |
| Context window | 20% | 24 | 24 | 37 |
| Overall | 100% | 30/100 | 40/100 | 28/100 |
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 | Magistral MediumMistral AI | QVQ MaxAlibaba (Qwen) | Qwen3-Coder 480B-A35B InstructAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $2.00 | $1.20 (best) | $1.50 |
| Output | $5.00 | $4.80 (best) | $7.50 |
| Cached input | — | — | — |
| Blended (3:1) | $2.75 | $2.10 (best) | $3.00 |
| Long-context rate | Same rate | Same rate | Over 32K: $2.70 / $13.50 |
| Price source | Official Mistral API | Official Alibaba API | Official Alibaba API |
| Limits | |||
| Context window | 128,000 tokens | 131,072 tokens | 262,144 tokens (best) |
| Max output | 16,384 tokens | 8,192 tokens | 65,536 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | magistral-medium-latest | qvq-max | qwen3-coder-480b-a35b-instruct |
| API providers | 4 | 1 | 7 (best) |
| Released | Mar 17, 2025 | Mar 25, 2025 | Apr 2025 |
| Knowledge cutoff | Jun 2025 | Apr 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.
- Magistral Medium$30.00
- QVQ Max$21.60
- Qwen3-Coder 480B-A35B Instruct$30.00
Which should you choose?
Which is better: Magistral Medium, QVQ Max or Qwen3-Coder 480B-A35B Instruct?
QVQ Max is the better all-round choice, scoring 40/100 against Magistral Medium (30) and Qwen3-Coder 480B-A35B Instruct (28). It leads on price and inputs & features. Qwen3-Coder 480B-A35B Instruct 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, Magistral Medium, QVQ Max or Qwen3-Coder 480B-A35B Instruct?
QVQ Max is cheaper at $1.20 input / $4.80 output per million tokens (official Alibaba API price). Magistral Medium costs $2.00 input / $5.00 output per million tokens (official Mistral API price); Qwen3-Coder 480B-A35B Instruct costs $1.50 input / $7.50 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $2.10 per million tokens for QVQ Max versus $2.75 for Magistral Medium (1.3× as much) and $3.00 for Qwen3-Coder 480B-A35B Instruct (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Magistral Medium has not been scored yet, QVQ Max has not been scored yet and Qwen3-Coder 480B-A35B Instruct has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Magistral Medium, QVQ Max and Qwen3-Coder 480B-A35B Instruct 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-Coder 480B-A35B Instruct has the largest context window at 262,144 tokens, against 131,072 for QVQ Max and 128,000 for Magistral Medium. Maximum output per response: Magistral Medium up to 16,384, QVQ Max up to 8,192, Qwen3-Coder 480B-A35B Instruct up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Magistral Medium accepts text; QVQ Max accepts text and images; Qwen3-Coder 480B-A35B Instruct accepts text. QVQ Max handles the widest range of inputs.
Are any of these open source?
Qwen3-Coder 480B-A35B Instruct publishes its weights and can be self-hosted; Magistral Medium and QVQ Max is proprietary.
Which is newer?
Qwen3-Coder 480B-A35B Instruct is the newest, released Apr 2025. QVQ Max came out Mar 25, 2025; Magistral Medium came out Mar 17, 2025. Knowledge cutoff: Magistral Medium Jun 2025, QVQ Max Apr 2024, Qwen3-Coder 480B-A35B Instruct 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.
