Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Mistral Medium 3.5 | Qwen3 Coder 480B A35B Instruct |
|---|---|---|
| Input ($/M tokens) | $1.5 | $1.5 |
| Output ($/M tokens) | $7.5 | $7.5 |
Verdict. Mistral Medium 3.5 wins the overall benchmark matchup 2–0 across 2 overlapping categories, but raw benchmark score is only one input to the decision.
Pricing. Both models sit in the mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, Qwen3 Coder 480B A35B Instruct is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Qwen3 Coder 480B A35B Instruct makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Mistral Medium 3.5 is strongest on Coding Index (46.9), Intelligence Index (30.4). Qwen3 Coder 480B A35B Instruct leads on Intelligence Index (18.2).
Speed. On throughput, Mistral Medium 3.5 generates tokens at 132 tok/s versus 66 tok/s — about 50% faster. On time-to-first-token, Mistral Medium 3.5 responds in 2280ms vs 3160ms, which matters most for chat-style UIs.
Provider. Mistral and Alibaba sell to overlapping but distinct developer audiences: Mistral tends to ship frontier reasoning models with premium positioning, while Alibaba often prices more aggressively. Your existing vendor relationships, billing, and SLA preferences may matter as much as the raw numbers above.
Workload cost. Workload scenarios (per million requests at 30M input + 15M output tokens): Mistral Medium 3.5 costs $157.50 ($1890/year); Qwen3 Coder 480B A35B Instruct costs $157.50 ($1890/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Mistral Medium 3.5 ≈ $22.50/run, Qwen3 Coder 480B A35B Instruct ≈ $22.50/run. At agent/realtime scale (200M input / 100M output per million requests): Mistral Medium 3.5 ≈ $1050/run, Qwen3 Coder 480B A35B Instruct ≈ $1050/run.
Recommendation. Both models have legitimate use cases — the right answer depends on whether you are optimizing for benchmark ceiling, latency, or unit cost. Start with the cheaper / faster model, evaluate against your specific task, and only switch if the upgrade shows a meaningful lift.
Head-to-head deltas
Data from Artificial Analysis API — 12 benchmarks
Both models have similar pricing. Check the detailed breakdown above for input vs output token costs.
Mistral Medium 3.5 wins 2 out of 12 benchmarks compared to 0 for Qwen3 Coder 480B A35B Instruct. See the detailed benchmark chart above for per-category results.
Mistral Medium 3.5 generates tokens faster at 132 tok/s vs 66 tok/s. Mistral Medium 3.5 also has lower time-to-first-token (2.28s vs 3.16s).
Choose based on your priorities: both are similarly priced, Mistral Medium 3.5 for stronger benchmark performance, and Mistral Medium 3.5 for faster generation. For latency-sensitive apps, check the TTFT comparison above.