For coding agents, GPT-5.6 Terra costs 3.1x as much as GLM 4.6 per request ($0.046 vs $0.015 on our measured traffic), because GPT-5.6 Terra lists at $2 input, $0.20 cached input and $12 output per million tokens against $0.50, $0.10 and $2 for GLM 4.6, and GPT-5.6 Terra charges more for prompts over 272K tokens.
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| Cost at list price | GLM 4.6 | GPT-5.6 Terra |
|---|---|---|
| Prompt under 100K tokens50% of requests, 87% of input cached | $0.0100 | $0.032 |
| Prompt of 100K to 272K39% of requests, 88% of input cached | $0.023 | $0.069 |
| Prompt over 272K tokens11% of requests, 86% of input cached | n/a | n/a |
| Average request | $0.015 | $0.046 |
| 100 requests | $1.47 | $4.61 |
| Median session16 requests; a session ends after 10 idle minutes | $0.17 | $0.55 |
| A month of regular usemedian of 20 users active on 5+ days | $15.56 | $52.31 |
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. Both models are priced on the requests up to 205K tokens that fit in both context windows; band shares above describe all requests.
| Artificial Analysis | GLM 4.6 | GPT-5.6 Terra |
|---|---|---|
| Intelligence Index10 evaluations, 0 to 100 | 19 (estimate) | 42 |
| Terminal-Bench 4.0agentic coding in a terminal | n/a | 35.4% |
| Output speedmedian | 36 tokens/s | 135 tokens/s |
| Time to first answer tokenincludes thinking time | 59 s | 2.2 min |
Source: Artificial Analysis (artificialanalysis.ai). Measured variants: GLM-4.6 (Reasoning); GPT-5.6 Terra (Max), speed on OpenAI. Fetched October 13, 2026. Artificial Analysis runs Terminal-Bench 4.0 in its own setup, so its scores differ from the tbench.ai leaderboard.
GLM 4.6's 205K window cannot take 20% of coding-agent requests, so the comparison uses only requests both can take. The price is OpenRouter's listed rate on October 13, 2026, which can be a third-party host's; Z.AI's own API may charge differently. GPT-5.6 Terra scores clearly higher on the benchmarks above, so it may finish hard tasks in fewer steps.
Pick a winner in each dimension. You can change your vote any time.
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 Terra: model ID, providers and agent config
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