Side-by-side comparison of pricing, 12 benchmarks, and generation speed.
| Metric | Llama 4 Scout | Mixtral 8x7B Instruct |
|---|---|---|
| Input ($/M tokens) | $0.19 | $0.45 |
| Output ($/M tokens) | $0.68 | $0.7 |
Verdict. Llama 4 Scout 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 budget bracket for output-token pricing. At 1.0× the per-million-token cost, Llama 4 Scout is meaningfully cheaper if your traffic is output-heavy (long completions, document generation, agent loops). Llama 4 Scout makes more sense when output volume is low and absolute reasoning quality justifies the premium.
Strengths. Llama 4 Scout is strongest on Coding Index (8.2), Intelligence Index (6.5). Mixtral 8x7B Instruct leads on Intelligence Index (5.1).
Speed. Speed data is incomplete for this pair; benchmark and price should decide.
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 4 Scout costs $15.90 ($191/year); Mixtral 8x7B Instruct costs $24.00 ($288/year). At a smaller 5M-input/2M-output scale (single-developer tool or prototype): Llama 4 Scout ≈ $2.31/run, Mixtral 8x7B Instruct ≈ $3.65/run. At agent/realtime scale (200M input / 100M output per million requests): Llama 4 Scout ≈ $106/run, Mixtral 8x7B Instruct ≈ $160/run. Llama 4 Scout 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.
Data from Artificial Analysis API — 12 benchmarks
Llama 4 Scout is cheaper overall. Its blended price (3:1 input/output ratio) is $0.31/M tokens vs $0.51/M for Mixtral 8x7B Instruct.
Llama 4 Scout wins 2 out of 12 benchmarks compared to 0 for Mixtral 8x7B Instruct. See the detailed benchmark chart above for per-category results.
Llama 4 Scout generates tokens faster at 121 tok/s vs — tok/s. Llama 4 Scout also has lower time-to-first-token (0.85s vs —s).
Choose based on your priorities: Llama 4 Scout for lower cost, Llama 4 Scout for stronger benchmark performance, and Llama 4 Scout for faster generation. For latency-sensitive apps, check the TTFT comparison above.