Llama 3.2 1B Instruct vs Mistral Large 3 675B Instruct
Llama 3.2 1B Instruct (2024) and Mistral Large 3 675B Instruct (2025) are compact production models from AI at Meta and MistralAI. Llama 3.2 1B Instruct ships a 128k-token context window, while Mistral Large 3 675B Instruct ships a 128k-token context window. On MMLU PRO, Mistral Large 3 675B Instruct leads by 65.5 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.
Llama 3.2 1B Instruct is ~1752% cheaper at $0.03/1M; pay for Mistral Large 3 675B Instruct only for vision-heavy evaluation.
Decision scorecard
Local evidence first| Signal | Llama 3.2 1B Instruct | Mistral Large 3 675B Instruct |
|---|---|---|
| Best for | provider-routed production | multimodal apps and provider-routed production |
| Decision fit | Coding, RAG, and Long context | Coding, RAG, and Agents |
| Context window | 128k | 128k |
| Cheapest output | $0.20/1M tokens | $1.50/1M tokens |
| Provider routes | 7 tracked | 5 tracked |
| Shared benchmarks | 3 rows | MMLU PRO leader |
Decision tradeoffs
- Llama 3.2 1B Instruct has the lower cheapest tracked output price at $0.20/1M tokens.
- Llama 3.2 1B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
- Local decision data tags Llama 3.2 1B Instruct for Coding, RAG, and Long context.
- Mistral Large 3 675B Instruct holds a shared-benchmark lead on MMLU PRO, ahead by 65.5 points.
- Mistral Large 3 675B Instruct uniquely exposes Vision and Multimodal in local model data.
- Local decision data tags Mistral Large 3 675B Instruct 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 3.2 1B Instruct
$71.85
Cheapest tracked route/tier: Cloudflare Workers AI
Mistral Large 3 675B Instruct
$775
Cheapest tracked route/tier: AWS Bedrock
Estimated monthly gap: $703. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on AWS Bedrock, NVIDIA NIM, and Vercel AI Gateway; start route-level A/B tests there.
- Mistral Large 3 675B Instruct is $1.30/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Mistral Large 3 675B Instruct adds Vision and Multimodal in local capability data.
- Provider overlap exists on NVIDIA NIM, AWS Bedrock, and Vercel AI Gateway; start route-level A/B tests there.
- Llama 3.2 1B Instruct is $1.30/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Vision and Multimodal before moving production traffic.
Specs
| Specification | ||
|---|---|---|
| Released | 2024-09-25 | 2025-12-01 |
| Context window | 128k | 128k |
| Parameters | 1.23B | 675B |
| Architecture | decoder only | decoder only |
| License | Llama 3 Community | Mistral License |
| Openness | Open weights | Open weights |
| Commercial use | Commercial use with conditions | Non-commercial only |
| Knowledge cutoff | 2023-12 | 2024-11 |
Pricing and availability
| Pricing attribute | Llama 3.2 1B Instruct | Mistral Large 3 675B Instruct |
|---|---|---|
| Input price | $0.03/1M tokens | $0.50/1M tokens |
| Output price | $0.20/1M tokens | $1.50/1M tokens |
| Providers |
Capabilities
| Capability | Llama 3.2 1B Instruct | Mistral Large 3 675B Instruct |
|---|---|---|
| Vision | No | Yes |
| Multimodal | No | Yes |
| Reasoning | No | No |
| Function calling | No | No |
| Tool use | No | No |
| Structured outputs | Yes | Yes |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
| Benchmark | Llama 3.2 1B Instruct | Mistral Large 3 675B Instruct |
|---|---|---|
| MMLU PRO | 20.0 | 85.5 |
| Google-Proof Q&A | 25.6 | 43.9 |
| HumanEval | 28.1 | 92.0 |
Deep dive
On shared benchmark coverage, MMLU PRO has Llama 3.2 1B Instruct at 20 and Mistral Large 3 675B Instruct at 85.5, with Mistral Large 3 675B Instruct ahead by 65.5 points; Google-Proof Q&A has Llama 3.2 1B Instruct at 25.6 and Mistral Large 3 675B Instruct at 43.9, with Mistral Large 3 675B Instruct ahead by 18.3 points; HumanEval has Llama 3.2 1B Instruct at 28.1 and Mistral Large 3 675B Instruct at 92, with Mistral Large 3 675B Instruct ahead by 63.9 points. The largest visible gap is 65.5 points on MMLU PRO, 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 vision: Mistral Large 3 675B Instruct and multimodal input: Mistral Large 3 675B Instruct. Both models share 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 3.2 1B Instruct lists $0.03/1M input and $0.20/1M output tokens on the cheapest tracked provider, while Mistral Large 3 675B Instruct lists $0.50/1M input and $1.50/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Llama 3.2 1B Instruct lower by about $0.72 per million blended tokens. Availability is 7 providers versus 5, so concentration risk also matters.
Choose Llama 3.2 1B Instruct when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Mistral Large 3 675B Instruct 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 3.2 1B Instruct or Mistral Large 3 675B Instruct?
Llama 3.2 1B Instruct supports 128k tokens, while Mistral Large 3 675B Instruct 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 3.2 1B Instruct or Mistral Large 3 675B Instruct?
Llama 3.2 1B Instruct is cheaper on tracked token pricing. Llama 3.2 1B Instruct costs $0.03/1M input and $0.20/1M output tokens. Mistral Large 3 675B Instruct costs $0.50/1M input and $1.50/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is Llama 3.2 1B Instruct or Mistral Large 3 675B Instruct open source?
Llama 3.2 1B Instruct is listed under Llama 3 Community. Mistral Large 3 675B Instruct 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 3.2 1B Instruct or Mistral Large 3 675B Instruct?
Mistral Large 3 675B Instruct has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for multimodal input, Llama 3.2 1B Instruct or Mistral Large 3 675B Instruct?
Mistral Large 3 675B Instruct has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run Llama 3.2 1B Instruct and Mistral Large 3 675B Instruct?
Llama 3.2 1B Instruct is available on Cloudflare Workers AI, OpenRouter, Fireworks AI, NVIDIA NIM, and Bitdeer AI. Mistral Large 3 675B Instruct is available on AWS Bedrock, NVIDIA NIM, Mistral AI Studio, Microsoft Foundry, and Vercel AI Gateway. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-06-04. Data sourced from public model cards and provider documentation.