Llama 4 Maverick 17B Instruct FP8 vs Mistral Large 2
Llama 4 Maverick 17B Instruct FP8 (2025) and Mistral Large 2 (2025) are compact production models from AI at Meta and MistralAI. Llama 4 Maverick 17B Instruct FP8 ships a 1m-token context window, while Mistral Large 2 ships a 128k-token context window. On MMLU PRO, Llama 4 Maverick 17B Instruct FP8 leads by 10.8 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 4 Maverick 17B Instruct FP8 is ~220% cheaper at $0.15/1M; pay for Mistral Large 2 only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | Llama 4 Maverick 17B Instruct FP8 | Mistral Large 2 |
|---|---|---|
| Best for | multimodal apps, long-context analysis, and provider-routed production | multimodal apps, tool-calling agents, and provider-routed production |
| Decision fit | Coding, RAG, and Agents | Coding, RAG, and Agents |
| Context window | 1m | 128k |
| Cheapest output | $0.60/1M tokens | $2.40/1M tokens |
| Provider routes | 10 tracked | 3 tracked |
| Shared benchmarks | MMLU PRO leader | 3 shared |
Decision tradeoffs
- Llama 4 Maverick 17B Instruct FP8 holds a shared-benchmark lead on MMLU PRO, ahead by 10.8 points.
- Llama 4 Maverick 17B Instruct FP8 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- Llama 4 Maverick 17B Instruct FP8 has the lower cheapest tracked output price at $0.60/1M tokens.
- Llama 4 Maverick 17B Instruct FP8 has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 4 Maverick 17B Instruct FP8 for Coding, RAG, and Agents.
- Mistral Large 2 holds a shared-benchmark lead on HumanEval, ahead by 7.4 points.
- Mistral Large 2 uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags Mistral Large 2 for Coding, RAG, and Agents.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Llama 4 Maverick 17B Instruct FP8
$270
Cheapest tracked route/tier: OpenRouter
Mistral Large 2
$984
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $714. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Mistral Large 2 is $1.80/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Mistral Large 2 adds Function calling and Tool use in local capability data.
- Provider overlap exists on AWS Bedrock; start route-level A/B tests there.
- Llama 4 Maverick 17B Instruct FP8 is $1.80/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-04-05 | 2025-11-25 |
| Context window | 1m | 128k |
| Parameters | 400B (17B active) | 123B |
| Architecture | Mixture of Experts | Decoder Only |
| License | Llama 4 Community | Mistral License |
| Openness | Open weights | Open weights |
| Commercial use | Commercial use: conditional | Commercial use: non-commercial |
| Knowledge cutoff | 2024-08 | 2025-07 |
Pricing and availability
| Pricing attribute | Llama 4 Maverick 17B Instruct FP8 | Mistral Large 2 |
|---|---|---|
| Input price | $0.15/1M tokens | $0.48/1M tokens |
| Output price | $0.60/1M tokens | $2.40/1M tokens |
| Providers |
Capabilities
| Capability | Llama 4 Maverick 17B Instruct FP8 | Mistral Large 2 |
|---|---|---|
| Vision | Yes | Yes |
| Multimodal | Yes | Yes |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 4 Maverick 17B Instruct FP8 | Mistral Large 2 |
|---|---|---|
| MMLU PRO | 80.5 | 69.7 |
| HumanEval | 77.4 | 84.8 |
| Chatbot Arena | 1365.0 | 1265.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 4 Maverick 17B Instruct FP8 at 80.5 and Mistral Large 2 at 69.7, with Llama 4 Maverick 17B Instruct FP8 ahead by 10.8 points; HumanEval has Llama 4 Maverick 17B Instruct FP8 at 77.4 and Mistral Large 2 at 84.8, with Mistral Large 2 ahead by 7.4 points; Chatbot Arena has Llama 4 Maverick 17B Instruct FP8 at 1365 and Mistral Large 2 at 1265, with Llama 4 Maverick 17B Instruct FP8 ahead by 100 points. The largest visible gap is 100 points on Chatbot Arena, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on function calling: Mistral Large 2 and tool use: Mistral Large 2. Both models share vision, multimodal input, and structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, Llama 4 Maverick 17B Instruct FP8 lists $0.15/1M input and $0.60/1M output tokens on the cheapest tracked provider, while Mistral Large 2 lists $0.48/1M input and $2.40/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 4 Maverick 17B Instruct FP8 lower by about $0.77 per million blended tokens. Availability is 10 providers versus 3, so concentration risk also matters.
Choose Llama 4 Maverick 17B Instruct FP8 when long-context analysis, larger context windows, and lower input-token cost are central to the workload. Choose Mistral Large 2 when vision-heavy evaluation are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, Llama 4 Maverick 17B Instruct FP8 or Mistral Large 2?
Llama 4 Maverick 17B Instruct FP8 supports 1m tokens, while Mistral Large 2 supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Which is cheaper, Llama 4 Maverick 17B Instruct FP8 or Mistral Large 2?
Llama 4 Maverick 17B Instruct FP8 is cheaper on tracked token pricing. Llama 4 Maverick 17B Instruct FP8 costs $0.15/1M input and $0.60/1M output tokens. Mistral Large 2 costs $0.48/1M input and $2.40/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 4 Maverick 17B Instruct FP8 or Mistral Large 2 open source?
Llama 4 Maverick 17B Instruct FP8 is listed under Llama 4 Community. Mistral Large 2 is listed under Mistral License. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for vision, Llama 4 Maverick 17B Instruct FP8 or Mistral Large 2?
Both Llama 4 Maverick 17B Instruct FP8 and Mistral Large 2 expose vision. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for multimodal input, Llama 4 Maverick 17B Instruct FP8 or Mistral Large 2?
Both Llama 4 Maverick 17B Instruct FP8 and Mistral Large 2 expose multimodal input. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Llama 4 Maverick 17B Instruct FP8 and Mistral Large 2?
Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. Mistral Large 2 is available on IBM watsonx, AWS Bedrock, and Mistral AI Studio. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-16. Data sourced from public model cards and provider documentation.