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

  1. GPT-6 LunaOpenAIRemove
  2. Transcribe 1 ProFish AudioRemove
  3. Gemma 4 26B A4B (Free)GoogleRemove
gpt-6-luna vs transcribe-1-pro vs gemma-4-26b-a4b-it:free
AttributeGPT-6 Lunagpt-6-lunaTranscribe 1 Protranscribe-1-proGemma 4 26B A4B (Free)gemma-4-26b-a4b-it:free
Pricing
Input$0.10 / 1M— Not priced per input token$0 / 1M
Output$0.50 / 1M— Not priced per output token$0 / 1M
Cache Write (5m)$0.10 / 1MNot applicable—
Cache Write (1h)$0.10 / 1MNot applicable—
Cache Read$0.10 / 1MNot applicable$0 / 1M
Web Search$0 / 1M$0 / 1M—
Cache Write——$0 / 1M
Context
Max context1.1MN/A262.1K
Max outputN/AN/AN/A
Capabilities
VisionYesNoYes
Function CallingYesNoYes
JSON ModeYesNoYes
StreamingYesNoYes
Catalogue
ProviderOpenAIFish AudioGoogle
Categorychatvoicechat
Charge typePay As You GoPay As You GoFree
Released—2026-09-24—
Description
SummaryGPT-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.Fish Audio Transcribe 1 Pro speech-to-text with speaker labels; transcripts include speaker tags such as <|speaker:0|>. Billed per second of audio.Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind, featuring 25.2B total parameters with only 3.8B activated per token—delivering near 31B-class quality at a fraction of the compute cost. It supports multimodal inputs including text, images, and video (up to 60s at 1fps). The model includes a 256K token context window, native function calling, configurable thinking/reasoning modes, and structured output support. Released under the Apache 2.0 license, it is well suited for efficient, production-ready multimodal and agentic applications.