Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Llama 3.2 Instruct 11B (Vision) | Mistral Small 3.2 |
|---|---|---|
| Input ($/M tokens) | $0.34 | $0.1 |
| Output ($/M tokens) | $0.34 | $0.3 |
Verdict. Mistral Small 3.2 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 budget bracket for output-token pricing. At 1.1× the per-million-token cost, Mistral Small 3.2 is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Mistral Small 3.2 makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Llama 3.2 Instruct 11B (Vision) is strongest on Intelligence Index (3.0). Mistral Small 3.2 leads on Coding Index (12.5), Intelligence Index (10.7).
Speed. On throughput, Mistral Small 3.2 generates tokens at 151 tok/s versus 40 tok/s — about 73% faster. On time-to-first-token, Mistral Small 3.2 responds in 860ms vs 1080ms, which matters most for chat-style UIs.
Provider. Meta and Mistral sell to overlapping but distinct developer audiences: Meta 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): Llama 3.2 Instruct 11B (Vision) costs $15.30 ($184/year); Mistral Small 3.2 costs $7.50 ($90/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Llama 3.2 Instruct 11B (Vision) ≈ $2.38/run, Mistral Small 3.2 ≈ $1.10/run. At agent/realtime scale (200M input / 100M output per million requests): Llama 3.2 Instruct 11B (Vision) ≈ $102/run, Mistral Small 3.2 ≈ $50/run. Mistral Small 3.2 becomes more attractive at higher volume — the absolute per-token pricing difference compounds when you ship at scale.
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
Mistral Small 3.2 is cheaper overall. Its blended price (3:1 input/output ratio) is $0.15/M tokens vs $0.34/M for Llama 3.2 Instruct 11B (Vision).
Mistral Small 3.2 wins 2 out of 12 benchmarks compared to 0 for Llama 3.2 Instruct 11B (Vision). See the detailed benchmark chart above for per-category results.
Mistral Small 3.2 generates tokens faster at 151 tok/s vs 40 tok/s. However, Mistral Small 3.2 has lower time-to-first-token (0.86s vs 1.08s).
Choose based on your priorities: Mistral Small 3.2 for lower cost, Mistral Small 3.2 for stronger benchmark performance, and Mistral Small 3.2 for faster generation. For latency-sensitive apps, check the TTFT comparison above.