LLM Reference

Mistral Large 2.1 (2411) vs Phi 3.5 MoE Instruct

Mistral Large 2.1 (2411) (2024) and Phi 3.5 MoE Instruct (2024) are compact production models from MistralAI and Microsoft Research. Mistral Large 2.1 (2411) ships a 128k-token context window, while Phi 3.5 MoE 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 2.1 (2411) is safer overall; choose Phi 3.5 MoE Instruct when provider fit matters.

Decision scorecard

Local evidence first
SignalMistral Large 2.1 (2411)Phi 3.5 MoE Instruct
Best fortool-calling agentsgeneral production evaluation
Decision fitRAG, Agents, and Long contextLong context
Context window128k128k
Cheapest output-$0.50/1M tokens
Provider routes0 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Mistral Large 2.1 (2411) when...
  • Mistral Large 2.1 (2411) uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
  • Local decision data tags Mistral Large 2.1 (2411) for RAG, Agents, and Long context.
Choose Phi 3.5 MoE Instruct when...
  • Phi 3.5 MoE Instruct has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags Phi 3.5 MoE Instruct for Long context.

Monthly cost at traffic

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

Mistral Large 2.1 (2411)

Unavailable

No complete token price in local provider data

Phi 3.5 MoE Instruct

$525

Cheapest tracked route/tier: Fireworks AI

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

Switch friction

Mistral Large 2.1 (2411) -> Phi 3.5 MoE Instruct
  • No overlapping tracked provider route is sourced for Mistral Large 2.1 (2411) and Phi 3.5 MoE Instruct; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.
Phi 3.5 MoE Instruct -> Mistral Large 2.1 (2411)
  • No overlapping tracked provider route is sourced for Phi 3.5 MoE Instruct and Mistral Large 2.1 (2411); plan for SDK, billing, or endpoint changes.
  • Mistral Large 2.1 (2411) adds Function calling, Tool use, and Structured outputs in local capability data.

Specs

Specification
Released2024-11-182024-08-20
Context window128k128k
Parameters123B16x3.8B (42B, 6.6B active)
Architecturedecoder onlydecoder only
LicenseMistral LicenseMIT(OSI)
OpennessOpen weightsOpen source
Commercial useNon-commercial onlyCommercial use allowed
Knowledge cutoff-2023-10

Pricing and availability

Pricing attributeMistral Large 2.1 (2411)Phi 3.5 MoE Instruct
Input price-$0.50/1M tokens
Output price-$0.50/1M tokens
Providers-

Capabilities

CapabilityMistral Large 2.1 (2411)Phi 3.5 MoE Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesNo
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 function calling: Mistral Large 2.1 (2411), tool use: Mistral Large 2.1 (2411), and structured outputs: Mistral Large 2.1 (2411). 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: Mistral Large 2.1 (2411) has no token price sourced yet and Phi 3.5 MoE Instruct has $0.50/1M input tokens. Provider availability is 0 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Mistral Large 2.1 (2411) when provider fit are central to the workload. Choose Phi 3.5 MoE Instruct when provider fit 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, Mistral Large 2.1 (2411) or Phi 3.5 MoE Instruct?

Mistral Large 2.1 (2411) supports 128k tokens, while Phi 3.5 MoE Instruct supports 128k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Mistral Large 2.1 (2411) or Phi 3.5 MoE Instruct open source?

Mistral Large 2.1 (2411) is listed under Mistral License. Phi 3.5 MoE Instruct is listed under MIT. 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 function calling, Mistral Large 2.1 (2411) or Phi 3.5 MoE Instruct?

Mistral Large 2.1 (2411) has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for tool use, Mistral Large 2.1 (2411) or Phi 3.5 MoE Instruct?

Mistral Large 2.1 (2411) has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for structured outputs, Mistral Large 2.1 (2411) or Phi 3.5 MoE Instruct?

Mistral Large 2.1 (2411) 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 Mistral Large 2.1 (2411) and Phi 3.5 MoE Instruct?

Mistral Large 2.1 (2411) is available on the tracked providers still being sourced. Phi 3.5 MoE Instruct is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-25. Data sourced from public model cards and provider documentation.