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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. GPT OSS 120BOpenAIRemove
  2. Gemini 3.8 FlashGoogleRemove
  3. GLM 5.3Z.AIRemove
  4. DeepSeek V4.1 FlashDeepSeekRemove

4 is the maximum. Remove one to add another.

gpt-oss-120b vs gemini-3.8-flash vs glm-5.3 vs deepseek-v4.1-flash
AttributeGPT OSS 120Bgpt-oss-120bGemini 3.8 Flashgemini-3.8-flashGLM 5.3glm-5.3DeepSeek V4.1 Flashdeepseek-v4.1-flash
Pricing
Input$0.15 / 1M$0.75 / 1M$1.40 / 1M$0.30 / 1M
Output$0.75 / 1M$3.75 / 1M$4.40 / 1M$1.20 / 1M
Cache Write (5m)$0.15 / 1M$0.75 / 1M$1.40 / 1M$0.30 / 1M
Cache Write (1h)$0.15 / 1M$0.75 / 1M$1.40 / 1M$0.30 / 1M
Cache Read$0.15 / 1M$0.75 / 1M$1.40 / 1M$0.30 / 1M
Web Search$0 / 1M$0 / 1M$0 / 1M$0 / 1M
Context
Max context131.1K1M1M1M
Max outputN/AN/AN/AN/A
Capabilities
VisionNoYesNoYes
Function CallingYesYesYesYes
JSON ModeYesYesYesYes
StreamingYesYesYesYes
Catalogue
ProviderOpenAIGoogleZ.AIDeepSeek
Categorychatchatchatchat
Charge typePay As You GoPay As You GoPay As You GoPay As You Go
Released
Description
Summarygpt-oss-120b is an open-weight 117B-parameter MoE model from OpenAI, built for advanced reasoning and production workloads. Only about 5.1B parameters are active per step, and it’s optimized to run on a single H100 using MXFP4 quantization. It supports adjustable reasoning depth, full chain-of-thought, and native agent features like tool use, function calling, browsing, and structured outputs.Gemini 3.8 Flash is Google's most intelligent Flash-class model, delivering significant improvements over Gemini 3.7 Flash across software engineering, agentic workflows, and complex multi-step reasoning. Designed to combine strong capability with Flash-tier efficiency, it is well suited for coding assistants, autonomous agents, and high-throughput production workflows that require responsive performance without sacrificing reasoning quality.GLM-5.3 is Z.ai's large-scale reasoning model designed for complex software engineering and long-horizon agentic workflows. It supports text input and output with a 1M-token context window, enabling sustained reasoning across large codebases and extended multi-step tasks. Building on GLM-5.2, it delivers stronger coding performance while improving the balance between capability and token efficiency, making it well suited for autonomous coding agents, large-scale engineering workflows, and complex task execution.DeepSeek V4.1 Flash is a cost-efficient sparse Mixture-of-Experts (MoE) model in DeepSeek's V4.1 family, optimized for coding, reasoning, and agentic workflows. Despite its efficiency-focused positioning, DeepSeek reports that it surpasses the previous V4 Pro in performance, inference speed, and overall task completion time. The model is particularly strong at long-horizon, multi-step execution, making it well suited for coding agents, complex problem solving, and autonomous workflows that must reliably carry tasks through to completion.