LLM Reference

Llama 3.3 70B vs Mistral Large 2

Llama 3.3 70B (2025) and Mistral Large 2 (2025) are compact production models from AI at Meta and MistralAI. Llama 3.3 70B ships a 8k-token context window, while Mistral Large 2 ships a 128k-token context window. On MMLU PRO, Llama 3.3 70B leads by 1.6 pts. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads.

Mistral Large 2 is ~88% cheaper at $0.48/1M; pay for Llama 3.3 70B only for vision-heavy evaluation.

Decision scorecard

Local evidence first
SignalLlama 3.3 70BMistral Large 2
Best formultimodal apps and tool-calling agentsmultimodal apps, tool-calling agents, and provider-routed production
Decision fitAgents, Vision, and ClassificationCoding, RAG, and Agents
Context window8k128k
Cheapest output$0.90/1M tokens$2.40/1M tokens
Provider routes1 tracked3 tracked
Shared benchmarksMMLU PRO leader1 shared

Decision tradeoffs

Choose Llama 3.3 70B when...
  • Llama 3.3 70B holds a shared-benchmark lead on MMLU PRO, ahead by 1.6 points.
  • Llama 3.3 70B has the lower cheapest tracked output price at $0.90/1M tokens.
  • Local decision data tags Llama 3.3 70B for Agents, Vision, and Classification.
Choose Mistral Large 2 when...
  • Mistral Large 2 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Mistral Large 2 has broader tracked provider coverage for fallback and procurement flexibility.
  • Mistral Large 2 uniquely exposes Structured outputs 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.

Lower estimate Llama 3.3 70B

Llama 3.3 70B

$945

Cheapest tracked route/tier: Fireworks AI

Mistral Large 2

$984

Cheapest tracked route/tier: AWS Bedrock

Estimated monthly gap: $39.00. Batch, cache, alternate speed tiers, and negotiated pricing are excluded from this local estimate.

Switch friction

Llama 3.3 70B -> Mistral Large 2
  • No overlapping tracked provider route is sourced for Llama 3.3 70B and Mistral Large 2; plan for SDK, billing, or endpoint changes.
  • Mistral Large 2 is $1.50/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
  • Mistral Large 2 adds Structured outputs in local capability data.
Mistral Large 2 -> Llama 3.3 70B
  • No overlapping tracked provider route is sourced for Mistral Large 2 and Llama 3.3 70B; plan for SDK, billing, or endpoint changes.
  • Llama 3.3 70B is $1.50/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
  • Check replacement coverage for Structured outputs before moving production traffic.

Specs

Specification
Released2025-12-092025-11-25
Context window8k128k
Parameters70B123B
ArchitectureDecoder OnlyDecoder Only
LicenseLlama 3 CommunityMistral License
OpennessOpen weightsOpen weights
Commercial useCommercial use: conditionalCommercial use: non-commercial
Knowledge cutoff2024-122025-07

Pricing and availability

Pricing attributeLlama 3.3 70BMistral Large 2
Input price$0.90/1M tokens$0.48/1M tokens
Output price$0.90/1M tokens$2.40/1M tokens
Providers

Capabilities

CapabilityLlama 3.3 70BMistral Large 2
VisionYesYes
MultimodalYesYes
ReasoningNoNo
Function callingYesYes
Tool useYesYes
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

BenchmarkLlama 3.3 70BMistral Large 2
MMLU PRO71.369.7

Deep dive

On shared benchmark coverage, MMLU PRO has Llama 3.3 70B at 71.3 and Mistral Large 2 at 69.7, with Llama 3.3 70B ahead by 1.6 points. The largest visible gap is 1.6 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 structured outputs: Mistral Large 2. Both models share vision, multimodal input, function calling, and tool use, 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 3.3 70B lists $0.90/1M input and $0.90/1M 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 3.3 70B lower by about $0.16 per million blended tokens. Availability is 1 providers versus 3, so concentration risk also matters.

Choose Llama 3.3 70B when vision-heavy evaluation are central to the workload. Choose Mistral Large 2 when long-context analysis, larger context windows, and lower input-token cost 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 3.3 70B or Mistral Large 2?

Mistral Large 2 supports 128k tokens, while Llama 3.3 70B supports 8k 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 3.3 70B or Mistral Large 2?

Llama 3.3 70B is cheaper on tracked token pricing. Llama 3.3 70B costs $0.90/1M input and $0.90/1M 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 3.3 70B or Mistral Large 2 open source?

Llama 3.3 70B is listed under Llama 3 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 3.3 70B or Mistral Large 2?

Both Llama 3.3 70B 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 3.3 70B or Mistral Large 2?

Both Llama 3.3 70B 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 3.3 70B and Mistral Large 2?

Llama 3.3 70B is available on Fireworks AI. 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.

Continue comparing

Last reviewed: 2026-06-16. Data sourced from public model cards and provider documentation.