For coding agents, Llama 4 Maverick costs 1.1x as much as GPT-5.6 Luna per request ($0.0095 vs $0.0084 on our measured traffic), because Llama 4 Maverick lists at $0.188 input, $0.05 cached input and $0.653 output per million tokens against $0.20, $0.02 and $1.20 for GPT-5.6 Luna, and GPT-5.6 Luna charges more for prompts over 272K tokens.
Run GPT-5.6 Luna and GPT-6 Luna in your agent from $19/month
See plans| Cost at list price | GPT-5.6 Luna | Llama 4 Maverick |
|---|---|---|
| Prompt under 100K tokens50% of requests, 87% of input cached | $0.0032 | $0.0043 |
| Prompt of 100K to 272K39% of requests, 88% of input cached | $0.0080 | $0.012 |
| Prompt over 272K tokens11% of requests, 86% of input cached | $0.034 | $0.026 |
| Average request | $0.0084 | $0.0095 |
| 100 requests | $0.84 | $0.95 |
| Median session16 requests; a session ends after 10 idle minutes | $0.092 | $0.11 |
| A month of regular usemedian of 20 users active on 5+ days | $11.83 | $15.76 |
Each logged request priced at the listed rates above for its own token counts, including cache reads and any higher rate for long prompts. Average output: 698 tokens per request.
| Artificial Analysis | GPT-5.6 Luna | Llama 4 Maverick |
|---|---|---|
| Intelligence Index10 evaluations, 0 to 100 | 37 | 10 (estimate) |
| Terminal-Bench 4.0agentic coding in a terminal | 11.6% | 0.0% |
| Output speedmedian | 123 tokens/s | 44 tokens/s |
| Time to first answer tokenincludes thinking time | 117 s | 1.1 s |
Source: Artificial Analysis (artificialanalysis.ai). Measured variants: GPT-5.6 Luna (Max), speed on OpenAI; Llama 4 Maverick. Fetched October 13, 2026. Artificial Analysis runs Terminal-Bench 4.0 in its own setup, so its scores differ from the tbench.ai leaderboard.
87% of agent input is read from cache, and Llama 4 Maverick charges $0.05 per million for it against $0.02. GPT-5.6 Luna is superseded: GPT-6 Luna costs $0.0041 per request. The price is OpenRouter's listed rate on October 13, 2026, which can be a third-party host's; Meta's own API may charge differently.
Pick a winner in each dimension. You can change your vote any time. 1 vote cast so far.
Correctness and depth of what it produces
Tool calls, instruction-following, and multi-step tasks
Tokens per second and time-to-first-token
How much capability you get per dollar
Consistent results: fewer refusals, loops and format breaks
Setting it up? GPT-5.6 Luna: model ID, providers and agent config
The agent matters as much as the model. Compare AI agents →
Current Claude, GPT, Gemini and open models are included with Standard Compute