LLM Reference

Mistral Medium 3.5 vs Sarvam 30B

Mistral Medium 3.5 (2026) and Sarvam 30B (2026) are frontier reasoning models from MistralAI and Sarvam.ai. Mistral Medium 3.5 ships a 256k-token context window, while Sarvam 30B ships a 66k-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. It focuses on practical selection signals rather than broad model-family marketing.

Mistral Medium 3.5 is safer overall; choose Sarvam 30B when provider fit matters.

Decision scorecard

Local evidence first
SignalMistral Medium 3.5Sarvam 30B
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentstool-calling agents
Decision fitCoding, RAG, and AgentsAgents and JSON / Tool use
Context window256k66k
Cheapest output$7.50/1M tokens-
Provider routes3 tracked0 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Mistral Medium 3.5 when...
  • Mistral Medium 3.5 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Mistral Medium 3.5 has broader tracked provider coverage for fallback and procurement flexibility.
  • Mistral Medium 3.5 uniquely exposes Vision, Multimodal, and Reasoning in local model data.
  • Local decision data tags Mistral Medium 3.5 for Coding, RAG, and Agents.
Choose Sarvam 30B when...
  • Local decision data tags Sarvam 30B for Agents and JSON / Tool use.

Monthly cost at traffic

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

Mistral Medium 3.5

$3,075

Cheapest tracked route/tier: Mistral AI Studio

Sarvam 30B

Unavailable

No complete token price in local provider data

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

Switch friction

Mistral Medium 3.5 -> Sarvam 30B
  • No overlapping tracked provider route is sourced for Mistral Medium 3.5 and Sarvam 30B; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
Sarvam 30B -> Mistral Medium 3.5
  • No overlapping tracked provider route is sourced for Sarvam 30B and Mistral Medium 3.5; plan for SDK, billing, or endpoint changes.
  • Mistral Medium 3.5 adds Vision, Multimodal, and Reasoning in local capability data.

Specs

Specification
Released2026-04-292026-03-22
Context window256k66k
Parameters128B30B (2.4B active)
Architecturedecoder onlymoe
LicenseProprietaryApache 2.0(OSI)
OpennessProprietaryOpen source
Commercial useCommercial use with conditionsCommercial use allowed
Knowledge cutoff-2025-06

Pricing and availability

Pricing attributeMistral Medium 3.5Sarvam 30B
Input price$1.50/1M tokens-
Output price$7.50/1M tokens-
Providers-

Capabilities

CapabilityMistral Medium 3.5Sarvam 30B
VisionYesNo
MultimodalYesNo
ReasoningYesNo
Function callingYesYes
Tool useYesYes
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 vision: Mistral Medium 3.5, multimodal input: Mistral Medium 3.5, reasoning mode: Mistral Medium 3.5, and structured outputs: Mistral Medium 3.5. Both models share 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.

Pricing coverage is uneven: Mistral Medium 3.5 has $1.50/1M input tokens and Sarvam 30B has no token price sourced yet. Provider availability is 3 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Mistral Medium 3.5 when reasoning depth, larger context windows, and broader provider choice are central to the workload. Choose Sarvam 30B when provider fit 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 Medium 3.5 or Sarvam 30B?

Mistral Medium 3.5 supports 256k tokens, while Sarvam 30B supports 66k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Mistral Medium 3.5 or Sarvam 30B open source?

Mistral Medium 3.5 is listed under Proprietary. Sarvam 30B is listed under Apache 2.0. 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, Mistral Medium 3.5 or Sarvam 30B?

Mistral Medium 3.5 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, Mistral Medium 3.5 or Sarvam 30B?

Mistral Medium 3.5 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 reasoning mode, Mistral Medium 3.5 or Sarvam 30B?

Mistral Medium 3.5 has the clearer documented reasoning mode signal in this comparison. If reasoning mode is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run Mistral Medium 3.5 and Sarvam 30B?

Mistral Medium 3.5 is available on Mistral AI Studio, OpenRouter, and Vercel AI Gateway. Sarvam 30B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.