Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Qwen3 Coder 480B A35B Instruct | Mistral Medium 3.5 |
|---|---|---|
| Input ($/M tokens) | $1.5 | $1.5 |
| Output ($/M tokens) | $7.5 | $7.5 |
Verdict. Mistral Medium 3.5 takes the aggregate benchmark matchup 2–0 across 2 categories. Real workloads usually care about a handful of specific tasks — see the per-benchmark table above.
Pricing. Both models sit in the mid-tier bracket for output-token pricing. At 1.0× the per-million-token cost, Mistral Medium 3.5 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Mistral Medium 3.5 makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Qwen3 Coder 480B A35B Instruct is strongest on Intelligence Index (18.2). Mistral Medium 3.5 leads on Coding Index (46.9), Intelligence Index (30.4).
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. Alibaba and Mistral sell to overlapping but distinct developer audiences: Alibaba tends to ship frontier reasoning models with premium positioning, while Mistral 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): Qwen3 Coder 480B A35B Instruct costs $157.50 ($1890/year); Mistral Medium 3.5 costs $157.50 ($1890/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Qwen3 Coder 480B A35B Instruct ≈ $22.50/run, Mistral Medium 3.5 ≈ $22.50/run. At agent/realtime scale (200M input / 100M output per million requests): Qwen3 Coder 480B A35B Instruct ≈ $1050/run, Mistral Medium 3.5 ≈ $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. However, Mistral Medium 3.5 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.