LLM Reference

Llama 3.1 Nemotron 70B Reward vs Mistral Large 3 675B Instruct

Llama 3.1 Nemotron 70B Reward (2024) and Mistral Large 3 675B Instruct (2025) are compact production models from NVIDIA AI and MistralAI. Llama 3.1 Nemotron 70B Reward ships a 4k-token context window, while Mistral Large 3 675B Instruct ships a 128k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Mistral Large 3 675B Instruct fits 32x more tokens; pick it for long-context work and Llama 3.1 Nemotron 70B Reward for tighter calls.

Decision scorecard

Local evidence first
SignalLlama 3.1 Nemotron 70B RewardMistral Large 3 675B Instruct
Best forgeneral production evaluationprovider-routed production
Decision fitClassificationCoding, RAG, and Agents
Context window4k128k
Cheapest output-$1.50/1M tokens
Provider routes1 tracked5 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Llama 3.1 Nemotron 70B Reward when...
  • Local decision data tags Llama 3.1 Nemotron 70B Reward for Classification.
Choose Mistral Large 3 675B Instruct when...
  • Mistral Large 3 675B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Mistral Large 3 675B Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Mistral Large 3 675B Instruct uniquely exposes Structured outputs 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 3.1 Nemotron 70B Reward

Unavailable

No complete token price in local provider data

Mistral Large 3 675B Instruct

$775

Cheapest tracked route/tier: AWS Bedrock

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

Llama 3.1 Nemotron 70B Reward -> Mistral Large 3 675B Instruct
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • Mistral Large 3 675B Instruct adds Structured outputs in local capability data.
Mistral Large 3 675B Instruct -> Llama 3.1 Nemotron 70B Reward
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2024-10-012025-12-01
Context window4k128k
Parameters70B675B
Architecturedecoder onlydecoder only
License11
Knowledge cutoff-2024-11

Pricing and availability

Pricing attributeLlama 3.1 Nemotron 70B RewardMistral Large 3 675B Instruct
Input price-$0.50/1M tokens
Output price-$1.50/1M tokens
Providers

Capabilities

CapabilityLlama 3.1 Nemotron 70B RewardMistral Large 3 675B Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on structured outputs: Mistral Large 3 675B Instruct. Both models share the core language-model surface, 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.

Pricing coverage is uneven: Llama 3.1 Nemotron 70B Reward has no token price sourced yet and Mistral Large 3 675B Instruct has $0.50/1M input tokens. Provider availability is 1 tracked routes versus 5. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Llama 3.1 Nemotron 70B Reward when provider fit are central to the workload. Choose Mistral Large 3 675B Instruct when long-context analysis, larger context windows, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency.

FAQ

Which has a larger context window, Llama 3.1 Nemotron 70B Reward or Mistral Large 3 675B Instruct?

Mistral Large 3 675B Instruct supports 128k tokens, while Llama 3.1 Nemotron 70B Reward supports 4k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Llama 3.1 Nemotron 70B Reward or Mistral Large 3 675B Instruct open source?

Llama 3.1 Nemotron 70B Reward is listed under 1. Mistral Large 3 675B Instruct is listed under 1. 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 structured outputs, Llama 3.1 Nemotron 70B Reward or Mistral Large 3 675B Instruct?

Mistral Large 3 675B Instruct has the clearer documented structured outputs signal in this comparison. If structured outputs is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Llama 3.1 Nemotron 70B Reward and Mistral Large 3 675B Instruct?

Llama 3.1 Nemotron 70B Reward is available on NVIDIA NIM. 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.

When should I pick Llama 3.1 Nemotron 70B Reward over Mistral Large 3 675B Instruct?

Mistral Large 3 675B Instruct fits 32x more tokens; pick it for long-context work and Llama 3.1 Nemotron 70B Reward for tighter calls. If your workload also depends on provider fit, start with Llama 3.1 Nemotron 70B Reward; if it depends on long-context analysis, run the same evaluation with Mistral Large 3 675B Instruct.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.