
LLM API Pricing Comparison - March 2026
Side-by-side LLM API pricing for GPT-5.4, Claude Opus 4.6, Gemini 3.1 Pro, DeepSeek V3.2, Grok 4, and 35+ models normalized to cost per million tokens.

Side-by-side LLM API pricing for GPT-5.4, Claude Opus 4.6, Gemini 3.1 Pro, DeepSeek V3.2, Grok 4, and 35+ models normalized to cost per million tokens.

Mistral AI secures $830M in debt financing from seven banks to build a 13,800-GPU Nvidia GB300 cluster near Paris, targeting 200MW of European compute by 2027.

Mistral's first open-weights TTS model clones voices from 3 seconds of audio, beats ElevenLabs on price, and arrives with real limitations worth knowing.

Mistral releases Voxtral, a pair of open-weights models covering speech recognition and text-to-speech that undercut OpenAI and ElevenLabs on price.

Mistral's new open-source Lean 4 agent scores higher than Claude Sonnet on formal proofs at one-fifteenth the cost, raising the bar for trustworthy AI code generation.

Mistral Small 4 packs reasoning, vision, and agentic coding into a 119B MoE under Apache 2.0 - a serious small-model contender at a price that's hard to ignore.

Mistral's new Forge platform lets enterprises train frontier-grade AI models entirely on proprietary data, without sending any of it to a third party.

Mistral AI's unified MoE model - 119B total parameters, 6B active per token, 128 experts, 256K context, configurable reasoning, Apache 2.0 license.

Mistral AI releases Small 4 - a 119B MoE with only 6B active parameters, 256K context, configurable reasoning, and Apache 2.0 license. Plus a new NVIDIA partnership to co-develop frontier open models.

Europe's most-funded AI startup is embedding engineers inside banks and consulting giants, borrowing Palantir's forward-deploy playbook to survive the frontier race.

Mistral Vibe 2.0 pairs the open-weight Devstral 2 model with a terminal-native coding agent. We tested it head-to-head against Claude Code and Codex.

Comparison of Kimi K2.5 and Mistral Large 3 - two large open-weight MoE models with 256K context, each representing a different vision for open AI.