vakati-tech.ai

// alternatives · October 2026

Mistral Large alternatives

Cheaper models that come close, budget substitutes, and the cheapest step up — chosen on published LiveBench scores and live list price, never on our opinion. Every model here supports tool calling, as Mistral Large does.

LiveBench hasn't published a run for Mistral Large. The strongest benchmarked model at a similar or lower price is GPT-6.1 Terra, scoring 77.8 overall.

Mistral Large: no published LiveBench run, $3.00 per 1M blended tokens, about $1,240/mo for a RAG assistant.

Benchmarked models at or below its price

Mistral Large has no published LiveBench run, so these are the highest-scoring benchmarked models priced no more than 25% above it — a known quantity to test against.

ModelOverallvs Mistral LargeBlended / 1MRAG assistantContext
GPT-6.1 Terraopenai

33% cheaper. Head to head →

77.8—$2.00−33%$720.00/mo1.1M
DeepSeek V4.1 Flash 1017deepseek

83% cheaper. Head to head →

74.0—$0.525−83%$194.40/mo1.0M
SpaceXAI: Grok 4.7x-ai

the same list price. Head to head →

70.1—$3.00$1,360/mo500K
Claude Haiku 5.5anthropic

93% cheaper. Head to head →

69.8—$0.200−93%$74.00/mo1M
MiMo-V2.6-Proxiaomi

82% cheaper. Head to head →

68.5—$0.544−82%$227.64/mo1.1M
SpaceXAI: Grok 4.6x-ai

the same list price. Head to head →

67.8—$3.00$1,360/mo500K

Mistral Large alternatives FAQ

What is the best alternative to Mistral Large?

GPT-6.1 Terra. 33% cheaper. Every suggestion supports tool calling, like Mistral Large.

How alternatives are chosen

  • Scores — LiveBench release 2026-10-25. Only models with a published run are suggested on quality; a missing model means “not evaluated”, not “worse”.
  • Prices — live list prices from OpenRouter, blended 3:1 input:output. Monthly figures price a RAG assistant with the published cached-input rate where there is one.
  • Same job — suggestions must support every capability Mistral Large has among tool calling and image input. Other listings of the same model (free or batch tiers) are variants, not alternatives, and are left out.

A few points on a public benchmark can hide large differences on your own tasks. Shortlist here, then decide with an eval — how to build one.