Llama 3.1 Nemotron 70B Reward vs Mistral Medium 3

Llama 3.1 Nemotron 70B Reward (2024) and Mistral Medium 3 (2025) are compact production models from NVIDIA AI and MistralAI. Llama 3.1 Nemotron 70B Reward ships a 4K-token context window, while Mistral Medium 3 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 Medium 3 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 Medium 3
Best forgeneral production evaluationmultimodal apps, tool-calling agents, and provider-routed production
Decision fitClassificationCoding, RAG, and Agents
Context window4K128K
Cheapest output-$2/1M tokens
Provider routes1 tracked5 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose Llama 3.1 Nemotron 70B Reward when...
  • Local decision data tags Llama 3.1 Nemotron 70B Reward for Classification.
Choose Mistral Medium 3 when...
  • Mistral Medium 3 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Mistral Medium 3 has broader tracked provider coverage for fallback and route flexibility.
  • Mistral Medium 3 uniquely exposes Vision, Multimodal, and JSON / Tool use in local model data.
  • Local decision data tags Mistral Medium 3 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 Medium 3

$820

Cheapest tracked route/tier: Mistral AI Studio

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

Switch friction

Llama 3.1 Nemotron 70B Reward -> Mistral Medium 3
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • Mistral Medium 3 adds Vision, Multimodal, and JSON / Tool use in local capability data.
Mistral Medium 3 -> Llama 3.1 Nemotron 70B Reward
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
  • Check replacement coverage for Vision, Multimodal, and JSON / Tool use before moving production traffic.

Specs

Specification
Released2024-10-012025-05-01
Context window4K128K
Parameters70B—
ArchitectureDecoder OnlyDecoder Only
LicenseNVIDIA Open ModelProprietary
OpennessOpen weightsProprietary
WeightsUnknownNot released
CodeUnknownUnknown
Commercial usePermittedRestricted
Knowledge cutoff-2025-03

Pricing and availability

Pricing attributeLlama 3.1 Nemotron 70B RewardMistral Medium 3
Input price-$0.40/1M tokens
Output price-$2/1M tokens
Providers

Capabilities

CapabilityLlama 3.1 Nemotron 70B RewardMistral Medium 3
VisionNoYes
MultimodalNoYes
ReasoningNoNo
JSON / Tool useNoYes
Structured outputsNoYes
Code executionNoYes
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on vision: Mistral Medium 3, multimodal input: Mistral Medium 3, JSON / Tool use: Mistral Medium 3, JSON / Tool use: Mistral Medium 3, structured outputs: Mistral Medium 3, and code execution: Mistral Medium 3. 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 Medium 3 has $0.40/1M 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 Medium 3 when coding workflow support, 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.

FAQ

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

Mistral Medium 3 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 Medium 3 open source?

Llama 3.1 Nemotron 70B Reward is listed under NVIDIA Open Model. Mistral Medium 3 is listed under Proprietary. 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 3.1 Nemotron 70B Reward or Mistral Medium 3?

Mistral Medium 3 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 3.1 Nemotron 70B Reward or Mistral Medium 3?

Mistral Medium 3 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.

Which is better for JSON / Tool use, Llama 3.1 Nemotron 70B Reward or Mistral Medium 3?

Mistral Medium 3 has the clearer documented JSON / Tool use signal in this comparison. If JSON / Tool use 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 Medium 3?

Llama 3.1 Nemotron 70B Reward is available on NVIDIA NIM. Mistral Medium 3 is available on NVIDIA NIM, Mistral AI Studio, Microsoft Foundry, OpenRouter, and GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-10-18. Data sourced from public model cards and provider documentation.