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Mixtral 8x7B Instruct v0.1 vs Phi 3.5 MoE Instruct

Mixtral 8x7B Instruct v0.1 (2023) and Phi 3.5 MoE Instruct (2024) are compact production models from MistralAI and Microsoft Research. Mixtral 8x7B Instruct v0.1 ships a 33K-token context window, while Phi 3.5 MoE Instruct ships a 128K-token context window. On pricing, Mixtral 8x7B Instruct v0.1 costs $0.15/1M input tokens versus $0.5/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.

Mixtral 8x7B Instruct v0.1 is ~233% cheaper at $0.15/1M; pay for Phi 3.5 MoE Instruct only for long-context analysis.

Specs

Specification
Released2023-12-102024-08-20
Context window33K128K
Parameters56B16x3.8B (42B, 6.6B active)
Architecturedecoder onlydecoder only
LicenseOpen SourceMIT
Knowledge cutoff2023-12-

Pricing and availability

Pricing attributeMixtral 8x7B Instruct v0.1Phi 3.5 MoE Instruct
Input price$0.15/1M tokens$0.5/1M tokens
Output price$0.45/1M tokens$0.5/1M tokens
Providers

Capabilities

CapabilityMixtral 8x7B Instruct v0.1Phi 3.5 MoE Instruct
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoNo
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint is close: both models cover the core production surface. 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.

For cost, Mixtral 8x7B Instruct v0.1 lists $0.15/1M input and $0.45/1M output tokens, while Phi 3.5 MoE Instruct lists $0.5/1M input and $0.5/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts Mixtral 8x7B Instruct v0.1 lower by about $0.26 per million blended tokens. Availability is 5 providers versus 1, so concentration risk also matters.

Choose Mixtral 8x7B Instruct v0.1 when provider fit, lower input-token cost, and broader provider choice are central to the workload. Choose Phi 3.5 MoE Instruct when long-context analysis and larger context windows 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, Mixtral 8x7B Instruct v0.1 or Phi 3.5 MoE Instruct?

Phi 3.5 MoE Instruct supports 128K tokens, while Mixtral 8x7B Instruct v0.1 supports 33K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Which is cheaper, Mixtral 8x7B Instruct v0.1 or Phi 3.5 MoE Instruct?

Mixtral 8x7B Instruct v0.1 is cheaper on tracked token pricing. Mixtral 8x7B Instruct v0.1 costs $0.15/1M input and $0.45/1M output tokens. Phi 3.5 MoE Instruct costs $0.5/1M input and $0.5/1M output tokens. Provider discounts or batch pricing can still change the final bill.

Is Mixtral 8x7B Instruct v0.1 or Phi 3.5 MoE Instruct open source?

Mixtral 8x7B Instruct v0.1 is listed under Open Source. 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.

Where can I run Mixtral 8x7B Instruct v0.1 and Phi 3.5 MoE Instruct?

Mixtral 8x7B Instruct v0.1 is available on Together AI, OctoML (Deprecated), AWS Bedrock, IBM watsonx, and DeepInfra. Phi 3.5 MoE Instruct is available on Fireworks AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

When should I pick Mixtral 8x7B Instruct v0.1 over Phi 3.5 MoE Instruct?

Mixtral 8x7B Instruct v0.1 is ~233% cheaper at $0.15/1M; pay for Phi 3.5 MoE Instruct only for long-context analysis. If your workload also depends on provider fit, start with Mixtral 8x7B Instruct v0.1; if it depends on long-context analysis, run the same evaluation with Phi 3.5 MoE Instruct.

Continue comparing

Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.