GitHub Copilot Pricing
GitHub Copilot charges from $1.20 per 1 million output tokens, depending on the model. GPT-5.6 Luna is the cheapest at $1.20/1M output and $0.200/1M input; its current flagship GPT-5.6 Sol costs $30.00/1M output. The largest context window is 1.1M tokens (GPT-5.4). Prices are USD, current as of August 11, 2026.
Last updated · synced weekly from the upstream model catalog
Cheapest input
$0.200/1M
GPT-5.4 nano
Cheapest output
$1.20/1M
GPT-5.6 Luna
Longest context
1.1M
GPT-5.4
Models priced
31
Avg $14.30/1M output
Pricing by model
All prices in USD per 1 million tokens. All 31 priced models, cheapest first.
| Model | Input / 1M | Output / 1M | Context |
|---|---|---|---|
| GPT-5.6 Luna VisionReasoningToolsCache | $0.200 | $1.20 | 1.1M |
| GPT-5.4 nano VisionReasoningToolsCache | $0.200 | $1.25 | 400K |
| GPT-5 Mini VisionReasoningToolsCache | $0.250 | $2.00 | 264K |
| Kimi K2.7 Code VisionReasoningToolsCache | $0.950 | $4.00 | 256K |
| GPT-5.4 mini VisionReasoningToolsCache | $0.750 | $4.50 | 400K |
| Mai Code 1 Flash Internal | $0.750 | $4.50 | 128K |
| MAI-Code-1-Flash ReasoningToolsCache | $0.750 | $4.50 | 256K |
| Claude Haiku 4.5 VisionReasoningToolsCache | $1.00 | $5.00 | 200K |
| Grok 4.5 VisionReasoningToolsCache | $2.00 | $6.00 | 500K |
| Gemini 3.6 Flash VisionReasoningToolsCache | $1.50 | $7.50 | 1.0M |
| GPT-4.1 VisionToolsCache | $2.00 | $8.00 | 128K |
| Gemini 3.5 Flash VisionReasoningToolsCache | $1.50 | $9.00 | 200K |
| Claude Sonnet 5 VisionReasoningToolsCache | $2.00 | $10.00 | 1.0M |
| Gemini 3.1 Pro Preview VisionReasoningToolsCache | $2.00 | $12.00 | 1.0M |
| GPT-5.6 Terra VisionReasoningToolsCache | $2.00 | $12.00 | 1.1M |
| GPT-5.2 VisionReasoningToolsCache | $1.75 | $14.00 | 400K |
| GPT-5.2 Codex VisionReasoningToolsCache | $1.75 | $14.00 | 400K |
| GPT-5.3 Codex VisionReasoningToolsCache | $1.75 | $14.00 | 400K |
| Claude Sonnet 4 VisionReasoningToolsCache | $3.00 | $15.00 | 216K |
| Claude Sonnet 4.5 VisionReasoningToolsCache | $3.00 | $15.00 | 200K |
| Claude Sonnet 4.6 VisionReasoningToolsCache | $3.00 | $15.00 | 200K |
| GPT-5.4 VisionReasoningToolsCache | $2.50 | $15.00 | 1.1M |
| Kimi K3 VisionReasoningToolsCache | $3.00 | $15.00 | 1.0M |
| Claude Opus 4.5 VisionReasoningToolsCache | $5.00 | $25.00 | 200K |
| Claude Opus 4.6 VisionReasoningToolsCache | $5.00 | $25.00 | 200K |
| Claude Opus 4.7 VisionReasoningToolsCache | $5.00 | $25.00 | 200K |
| Claude Opus 4.8 VisionReasoningToolsCache | $5.00 | $25.00 | 200K |
| Claude Opus 5 VisionReasoningToolsCache | $5.00 | $25.00 | 1.0M |
| GPT-5.5 VisionReasoningToolsCache | $5.00 | $30.00 | 1.1M |
| GPT-5.6 Sol VisionReasoningToolsCache | $5.00 | $30.00 | 1.1M |
| Claude Fable 5 VisionReasoningToolsCache | $10.00 | $50.00 | 1.0M |
Frequently asked questions
How much does GitHub Copilot cost per 1M tokens?
GitHub Copilot pricing starts at $1.20 per 1 million output tokens (GPT-5.6 Luna) across 31 models, with its current flagship GPT-5.6 Sol at $30.00. Older premium models in the catalog list higher. Rates current as of August 11, 2026.
What is the cheapest GitHub Copilot model?
GPT-5.6 Luna is the cheapest GitHub Copilot model on output tokens at $1.20 per 1M, while GPT-5.4 nano is cheapest on input at $0.200 per 1M. Which wins for you depends on your input-to-output ratio.
What is the largest GitHub Copilot context window?
GPT-5.4 has the largest context window in the GitHub Copilot catalog at 1.1M input tokens, with up to 128K output tokens per response.
Does GitHub Copilot support prompt caching?
Yes. GPT-5.4 nano reads cached input at $0.020 per 1M tokens, against $0.200 per 1M uncached. Caching pays off when a long system prompt or document is reused across many requests.
Which GitHub Copilot models support reasoning or vision?
The GitHub Copilot catalog includes 29 reasoning models, 29 vision models, 30 with tool calling. Reasoning models bill their internal thinking as output tokens, so they cost more per visible response than the headline rate suggests.
How do I calculate my actual GitHub Copilot bill?
Multiply your input tokens by the input rate and your output tokens by the output rate, both per million, then add retries and any conversation history resent on each turn. Calcaas does this against your real usage pattern and shows the margin left at your price point.
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What will this actually cost you?
Per-token rates only tell you half the story. Calcaas multiplies them by your real usage — prompt size, response length, retries and conversation history — then shows the margin left at your price point.
Open the free cost calculator