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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. Gemini 3.5 TranscribeGoogleRemove
  2. Gemma 4 26B A4B (Free)GoogleRemove
  3. GPT-6.1 SolOpenAIRemove
gemini-3.5-transcribe vs gemma-4-26b-a4b-it:free vs gpt-6.1-sol
AttributeGemini 3.5 Transcribegemini-3.5-transcribeGemma 4 26B A4B (Free)gemma-4-26b-a4b-it:freeGPT-6.1 Solgpt-6.1-sol
Pricing
Input— Not priced per input token$0 / 1M$2.00 / 1M
Output— Not priced per output token$0 / 1M$10.00 / 1M
Cache Write (5m)Not applicable—$2.00 / 1M
Cache Write (1h)Not applicable—$2.00 / 1M
Cache ReadNot applicable$0 / 1M$2.00 / 1M
Web Search$0 / 1M—$0 / 1M
Cache Write—$0 / 1M—
Context
Max context98.3K262.1K1M
Max outputN/AN/AN/A
Capabilities
VisionYesYesYes
Function CallingYesYesYes
JSON ModeNoYesYes
StreamingNoYesYes
Catalogue
ProviderGoogleGoogleOpenAI
Categoryvoicechatchat
Charge typePay As You GoFreePay As You Go
Released2026-09-25——
Description
SummaryGoogle Gemini 3.5 Transcribe speech-to-text. Billed per input and output token.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.GPT-6.1 Sol is an upgraded high-end model in OpenAI's GPT-6 series, positioned below the flagship GPT-6 Astra. It is optimized for agentic coding, computer use, document-heavy professional work, and multi-step business automation, delivering near-Astra-level capability at significantly lower cost. Compared with GPT-6 Sol, it offers improved factual reliability and stronger adherence to explicit constraints and user intent, making it well suited for complex, long-running agentic workflows where accurate and dependable execution is critical.