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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. Claude Sonnet 5.5AnthropicRemove
  2. Gemini 3.5 TranscribeGoogleRemove
  3. GPT-6 LunaOpenAIRemove
  4. MiniMax M2MiniMaxRemove

4 is the maximum. Remove one to add another.

claude-sonnet-5.5 vs gemini-3.5-transcribe vs gpt-6-luna vs minimax-m2
AttributeClaude Sonnet 5.5claude-sonnet-5.5Gemini 3.5 Transcribegemini-3.5-transcribeGPT-6 Lunagpt-6-lunaMiniMax M2minimax-m2
Pricing
Input$2.00 / 1M— Not priced per input token$0.10 / 1M$0.15 / 1M
Output$10.00 / 1M— Not priced per output token$0.50 / 1M$0.45 / 1M
Cache Write (5m)$2.50 / 1MNot applicable$0.10 / 1M$0.15 / 1M
Cache Write (1h)$4.00 / 1MNot applicable$0.10 / 1M$0.15 / 1M
Cache Read$0.20 / 1MNot applicable$0.10 / 1M$0.15 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context1M98.3K1.1M196.6K
Max outputN/AN/AN/AN/A
Capabilities
VisionYesYesYesYes
Function CallingYesYesYesYes
JSON ModeYesNoYesYes
StreamingYesNoYesYes
Catalogue
ProviderAnthropicGoogleOpenAIMiniMax
Categorychatvoicechatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released—2026-09-25——
Description
SummaryClaude Sonnet 5.5 is Anthropic's Sonnet-class model for well-scoped everyday work, serving as a direct upgrade to Sonnet 5. It excels at feature development, bug fixing, and creating polished documents, presentations, and spreadsheets, while offering clearer writing and communication than its predecessor.Google Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, optimized for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic tasks. It combines low-cost, responsive inference with the GPT-6 family’s improvements in factual reliability and clear, concise communication. At higher reasoning effort, GPT-6 Luna can also handle complex software engineering and computer-use workflows that previously required a Sol-tier model, making it a versatile choice for scalable production applications that need to balance speed, cost, and capability.MiniMax-M2 is a compact, high-efficiency model with 10B active (230B total) parameters, optimized for coding and agentic workflows. It delivers near-frontier reasoning and tool use, excels at multi-file coding tasks and compile-run-fix loops, and performs strongly on benchmarks like SWE-Bench and Terminal-Bench. It also handles long-horizon planning and recovery in agent evaluations, ranking among the top open models across reasoning domains. With fast inference and low cost, it’s ideal for large-scale agents and developer assistants — and works best when reasoning is preserved across turns.