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Compare models

Put up to 4 models beside each other — token prices, context windows, capabilities and provider, from the same catalogue the model pages read.

  1. Voxtral Small 24B 2507 STTMistral AIRemove
  2. GPT-6.1 TerraOpenAIRemove
  3. Gemini 4 CarbonGoogleRemove
voxtral-small-24b-2507-stt vs gpt-6.1-terra vs gemini-4-carbon
AttributeVoxtral Small 24B 2507 STTvoxtral-small-24b-2507-sttGPT-6.1 Terragpt-6.1-terraGemini 4 Carbongemini-4-carbon
Pricing
Input— Not priced per input token$1.00 / 1M$2.00 / 1M
Output— Not priced per output token$5.00 / 1M$10.00 / 1M
Cache Write (5m)Not applicable$1.00 / 1M$2.00 / 1M
Cache Write (1h)Not applicable$1.00 / 1M$2.00 / 1M
Cache ReadNot applicable$1.00 / 1M$2.00 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M
Context
Max contextN/A1M1M
Max outputN/AN/AN/A
Capabilities
VisionNoYesYes
Function CallingNoYesYes
JSON ModeNoYesYes
StreamingNoNoYes
Catalogue
ProviderMistral AIOpenAIGoogle
Categoryvoicechatchat
Charge typePay As You GoPay As You GoPay As You Go
Released2026-08-13——
Description
SummaryMistral AI Voxtral Small (24B) speech-to-text. Billed per second of audio.GPT-6.1 Terra is OpenAI’s mid-tier model in the GPT-6.1 series, designed to balance capability, speed, and cost efficiency. Positioned below GPT-6.1 Sol, it delivers strong performance across everyday agentic workflows, coding, and professional writing, with particular strengths in screenshot understanding and on-screen content analysis. Optimized for high-volume production workloads, GPT-6.1 Terra is well suited for coding assistants, visual interface analysis, workflow automation, and scalable agentic applications that require reliable performance at an accessible cost.Gemini 4 Carbon is Google's frontier multimodal reasoning model, designed for advanced coding, agentic workflows, and complex multi-step problem solving. It supports text, image, audio, video, and file inputs, enabling integrated reasoning and analysis across diverse modalities. Optimized for long-horizon execution and demanding professional workloads, Gemini 4 Carbon supports up to 1M output tokens through continuation and configurable reasoning effort levels (low, medium, high) to balance reasoning depth, latency, and cost. It is well suited for autonomous agents, software engineering, multimodal analysis, and large-scale workflow automation.