WritingmateWritingmate
Model Comparison

Mistral Small 3 vs Jev RouterWhich Is Better in 2026?

Mistral: Mistral Small 3 logoMistral AI•
Typesafe

Mistral Small 3 vs Jev Router: which should you choose in 2026?

Mistral Small 3 (by Mistral AI) and Jev Router (by Typesafe) are compared below. Here is how they stack up on benchmarks, price, and capabilities, and which one to pick in 2026.

There are not enough shared, protocol-compatible benchmark results to declare a performance leader.

Jev Router has the larger context window (1,000,000 tokens vs 32,768 tokens).

Choose Mistral Small 3 if…

  • • your own prompt tests favor its output; shared comparable evidence does not identify a unique advantage

Choose Jev Router if…

  • • you work with longer documents, transcripts, or codebases
  • • you need a model with explicit reasoning support
  • • you need image inputs

The benchmark count includes only results measured with a matching benchmark version and protocol. Arena scores are shown separately. Missing, preliminary, and incompatible data is not treated as a controlled win. Published point-score comparisons are labeled separately when protocol details are incomplete. For text-output models, the verdict also compares token pricing and context windows.

Chat with both models
vs

Performance benchmarks

Every value links to its source. A dash means that no reviewed result is available for that exact model and protocol.

Mistral Small 3 and Jev Router benchmark results
BenchmarkMistral Small 3Jev Router
AutomationBench-AA

A 657-task benchmark of multi-step work across simulated SaaS applications in six business domains. The Artificial Analysis protocol reports a guardrail-aware score and is distinct from both the public Zapier split and the unrelated dynamic AutoBench framework.

Guardrail-aware score

——
BrowseComp

A benchmark of difficult, verifiable information-seeking questions designed to measure an agent's ability to locate hard-to-find facts through web browsing.

Accuracy

——
OSWorld-Verified

A verified computer-use benchmark in which multimodal agents operate desktop applications and are graded from the resulting environment state.

Mean task reward

——
SWE-Bench Verified

A human-validated subset of real GitHub issues used to measure whether a coding agent can produce repository patches that resolve the associated tests.

Resolved

——
Terminal-Bench 2.1

Version 2.1 of the benchmark for completing realistic tasks in terminal environments. Harness, resource limits, and attempt count are part of the protocol.

Mean task success

——
AutoBench

A dynamic LLM evaluation framework in which models generate questions, answer them, and participate in reciprocal peer assessment. AutoBench is distinct from Zapier's AutomationBench.

Weighted peer-assessment score

——
GPQA Diamond

The highest-quality subset of Graduate-Level Google-Proof Q&A, designed to test expert-level scientific reasoning in biology, physics, and chemistry.

Accuracy

——
Humanity's Last Exam

A 2,500-question expert-level benchmark spanning dozens of academic fields. Tool-assisted and no-tools results are separate protocols and must not be merged.

Accuracy

——
Arena preference scores
Arena (Text)

Human preference score

1274 ±6
—

Benchmark sources

Reviewed evidence last updated 2026-08-09. Arena data last refreshed Oct 4, 2026.

Pricing, capabilities, and model facts

Mistral Small 3 and Jev Router model facts
FeatureMistral Small 3Jev Router
Context & model facts
DeveloperMistral AITypesafe
API providerMistralTypeSafe
Input context32,768 tokens1,000,000 tokens
Maximum output16,384 tokens—
Released——
Added to WritingmateJan 30, 2025Sep 25, 2026
LicenseNot availableNot available
Knowledge cutoff2023-10-31—
Capabilities
InputsTextAudio, File, Image, Text, Video
OutputsTextText
Provider endpoint accepts tool parametersNoYes
ReasoningNoYes
VisionNoYes
Image GenerationNoNo
Video GenerationNoNo
API pricing
Input (per 1M tokens)$0.05—
Output (per 1M tokens)$0.08—
Blended 3:1 input/output$0.0575—
API performance
p95 latencyNot measuredNot measured
Output throughputNot measuredNot measured
Writingmate shows API performance only when both models have enough observations from the same measurement window, prompt profile, and provider. Third-party latency values are not copied into this table.

Data sources

  • Writingmate model catalog (pricing, limits, and availability)

Catalog data last updated Sep 25, 2026.

Why Pay for Multiple Subscriptions?

Comparing Mistral Small 3 from Mistral AI with Jev Router from Typesafe? Instead of managing separate API keys and subscriptions, get both with Writingmate.

Subscription-plan access for Mistral Small 3 and Jev Router
PlanPriceMistral Small 3Jev RouterAI ImagesAI Video
Writingmate Pro
Most popular
$20/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreVEO 3.1, Kling 3.0
Writingmate Ultimate
Power users
$60/moIncludedIncludedNano Banana Pro, FLUX.2, DALL-E & moreVEO 3.1, Kling 3.0
View Plans & Pricing

Mistral Small 3 vs Jev Router FAQ

Which is better, Mistral Small 3 or Jev Router?

There are not enough shared, protocol-compatible benchmark results to declare a performance leader. Jev Router has the larger context window (1,000,000 tokens vs 32,768 tokens).

Which model is cheaper to use through an API?

A comparable blended token price is not available for both models. Check the API pricing rows for the values that are currently published.

Which model supports more context?

Jev Router has the larger context window (1,000,000 tokens vs 32,768 tokens).

Can I switch between Mistral Small 3 and Jev Router?

Yes. Use the model selector on this page to open any current Writingmate model comparison. You can also run the same prompt with both models in Writingmate.