GLM-5.2 vs Claude Opus 4.8: how close open weights get on coding

Z.ai's GLM-5.2 is an MIT-licensed open model built for long coding and agent sessions. Anthropic's Claude Opus 4.8 is a closed flagship known for long autonomous runs. Put side by side, they answer a practical question: how close can open weights get to a closed flagship on real coding work?

The short version: GLM-5.2 when you need long coding runs to stay cheap, Opus 4.8 when quality and consistency come first.

Specs and price

Prices are FastMetal's USD list as of October 25, 2026, rounded to the cent; the current figures are on the models page.

On a task of 100,000 input tokens and 10,000 output tokens, that's about $0.19 on GLM-5.2 and $0.79 on Opus 4.8. Output is where the gap is widest: Opus 4.8 costs nearly six times as much per output token, and agent runs are output-heavy.

Where each is stronger

GLM-5.2 is tuned for long coding and agent work. Reviews report 62.1 on SWE-bench Pro, ahead of GPT-5.5's 58.6. Its context window grew from 200K tokens in the previous generation to about 1M, enough to load a whole repository. Reviewers also put its coding performance level with or above GPT-5.5 at roughly a sixth of the cost, and the MIT license leaves you free to self-host or build on it.

Claude Opus 4.8 is the strongest model in Anthropic's Opus 4 generation. It is at its best on long autonomous agent runs, where it plans, delegates and checks its own work across many steps. It is also known for clear writing and close instruction-following.

What each gets wrong

GLM-5.2 is text only. It can't read images. On general reasoning and on precise reading of very long contexts, the common view is that the top closed models still lead.

Opus 4.8 is expensive, and long runs multiply that. The per-token price is high, and a long agent session burns a lot of tokens. For everyday light work it is overkill; a smaller model usually does the job for much less.

Which to use where

• GLM-5.2: long coding and refactoring jobs, commercial projects that need costs kept down, and anything where license freedom is a requirement.
• Claude Opus 4.8: autonomous agents where quality and consistency matter most, and work that needs image or PDF input.

Try both with one key

On FastMetal both are behind the same API key and the same balance. Change model and nothing else.

# GLM-5.2
curl https://api.fastmetal.ai/v1/chat/completions \
  -H "Authorization: Bearer $FASTMETAL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "glm-5.2", "messages": [{"role": "user", "content": "Hello"}]}'

# Claude Opus 4.8: same request, different model
curl https://api.fastmetal.ai/v1/chat/completions \
  -H "Authorization: Bearer $FASTMETAL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "anthropic-claude-opus-4-8", "messages": [{"role": "user", "content": "Hello"}]}'

FAQ

Which is better for coding? On benchmarks it's close: GLM-5.2 was reported ahead of GPT-5.5 on SWE-bench Pro. Opus 4.8 still leads on general reasoning and on precision over long contexts. Compare them on your own tasks.

How big is the price gap? GLM-5.2 costs $1.48 in and $4.64 out per million tokens on FastMetal, against $5.28 and $26.38 for Opus 4.8. Current prices are on the models page.

Which is better outside English? We couldn't find a published benchmark that isolates non-English quality for either model. If your work is mostly in another language, test with your own prompts.

Bottom line

GLM-5.2 for long coding runs on a budget, Claude Opus 4.8 for quality and consistency. On coding, open weights are now within reach of the closed flagships; whether the remaining gap matters depends on your work.

Both models, with current prices, are in the model catalog. Opus 4.8 against xAI's coding model is in Grok 4.5 vs Claude Opus 4.8.