LLM Reference

Llama 3.1 Nemotron Nano VL 8B v1 vs Mistral Medium 3 Instruct

Llama 3.1 Nemotron Nano VL 8B v1 (2025) and Mistral Medium 3 Instruct (2025) are compact production models from NVIDIA AI and MistralAI. Llama 3.1 Nemotron Nano VL 8B v1 ships a 4k-token context window, while Mistral Medium 3 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 Medium 3 Instruct fits 32x more tokens; pick it for long-context work and Llama 3.1 Nemotron Nano VL 8B v1 for tighter calls.

Decision scorecard

Local evidence first
SignalLlama 3.1 Nemotron Nano VL 8B v1Mistral Medium 3 Instruct
Best formultimodal appsmultimodal apps and provider-routed production
Decision fitVisionLong context and Vision
Context window4k128k
Cheapest output-$2/1M tokens
Provider routes1 tracked2 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose Llama 3.1 Nemotron Nano VL 8B v1 when...
  • Local decision data tags Llama 3.1 Nemotron Nano VL 8B v1 for Vision.
Choose Mistral Medium 3 Instruct when...
  • Mistral Medium 3 Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Mistral Medium 3 Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Mistral Medium 3 Instruct for Long context and Vision.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

Llama 3.1 Nemotron Nano VL 8B v1

Unavailable

No complete token price in local provider data

Mistral Medium 3 Instruct

$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 Nano VL 8B v1 -> Mistral Medium 3 Instruct
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.
Mistral Medium 3 Instruct -> Llama 3.1 Nemotron Nano VL 8B v1
  • Provider overlap exists on NVIDIA NIM; start route-level A/B tests there.

Specs

Specification
Released2025-03-012025-10-01
Context window4k128k
Parameters8B
ArchitectureDecoder OnlyDecoder Only
LicenseLlama 3 CommunityProprietary
OpennessOpen weightsProprietary
WeightsUnknownNot released
CodeUnknownUnknown
Commercial useCommercial use: conditionalCommercial use: conditional
Knowledge cutoff-2025-03

Pricing and availability

Pricing attributeLlama 3.1 Nemotron Nano VL 8B v1Mistral Medium 3 Instruct
Input price-$0.40/1M tokens
Output price-$2/1M tokens
Providers

Capabilities

CapabilityLlama 3.1 Nemotron Nano VL 8B v1Mistral Medium 3 Instruct
VisionYesYes
MultimodalYesYes
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint is close: both models cover vision and multimodal input. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

Pricing coverage is uneven: Llama 3.1 Nemotron Nano VL 8B v1 has no token price sourced yet and Mistral Medium 3 Instruct has $0.40/1M input tokens. Provider availability is 1 tracked routes versus 2. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Llama 3.1 Nemotron Nano VL 8B v1 when vision-heavy evaluation are central to the workload. Choose Mistral Medium 3 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 Nano VL 8B v1 or Mistral Medium 3 Instruct?

Mistral Medium 3 Instruct supports 128k tokens, while Llama 3.1 Nemotron Nano VL 8B v1 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 Nano VL 8B v1 or Mistral Medium 3 Instruct open source?

Llama 3.1 Nemotron Nano VL 8B v1 is listed under Llama 3 Community. Mistral Medium 3 Instruct 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 Nano VL 8B v1 or Mistral Medium 3 Instruct?

Both Llama 3.1 Nemotron Nano VL 8B v1 and Mistral Medium 3 Instruct 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 3.1 Nemotron Nano VL 8B v1 or Mistral Medium 3 Instruct?

Both Llama 3.1 Nemotron Nano VL 8B v1 and Mistral Medium 3 Instruct 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 3.1 Nemotron Nano VL 8B v1 and Mistral Medium 3 Instruct?

Llama 3.1 Nemotron Nano VL 8B v1 is available on NVIDIA NIM. Mistral Medium 3 Instruct is available on NVIDIA NIM and Mistral AI Studio. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Llama 3.1 Nemotron Nano VL 8B v1 over Mistral Medium 3 Instruct?

Mistral Medium 3 Instruct fits 32x more tokens; pick it for long-context work and Llama 3.1 Nemotron Nano VL 8B v1 for tighter calls. If your workload also depends on vision-heavy evaluation, start with Llama 3.1 Nemotron Nano VL 8B v1; if it depends on long-context analysis, run the same evaluation with Mistral Medium 3 Instruct.

Continue comparing

Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.