What is GLM-5.2 best for?
GLM-5.2 is best for budget agentic coding at scale. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and balanced speed.
Top open-weights coder — beats GPT-5.5 at a sixth of the cost.
Budget agentic coding at scale
You need frontier reasoning ceiling or launch-day verified benchmarks.
Announced June 13, 2026; pay-per-token API live June 16. Two reasoning modes ('thinking' and 'max thinking'). GLM Coding Plan: Lite $18/mo (~$12.60 effective yearly), Pro $72, Max $160.
SWE-bench Pro 62.1 — ahead of GPT-5.5 and close to Claude Opus 4.8 on agentic coding
AA Intelligence Index 51 in max-thinking mode — well above similar-size open-weight models
MIT-licensed weights with aggressive pricing: $1.40/$4.40 first-party, cheaper via third-party hosts
Clear gap to the closed frontier: AA Index 51 vs Claude Opus 5 (61) and GPT-5.6 Sol (59)
Z.ai published no benchmark numbers at launch — buyers depended on third-party evals that arrived weeks later
What people actually use GLM-5.2 for.
Agentic coding — 62.1 SWE-bench Pro, ahead of GPT-5.5 at ~1/6th the price
Coding-plan subscriptions from ~$12.60/mo effective for individual developers
Self-hosted or third-party-hosted deployments (DeepInfra from ~$0.75/1M input)
Budget agentic coding at scale. Start free — no card required.
Recommendations are made independently based on real-world use and public benchmarks. See our disclosures for details.
GLM-5.2 is best for budget agentic coding at scale. It is a strong fit when that workflow matters more than the tradeoffs around budget pricing and balanced speed.
You need frontier reasoning ceiling or launch-day verified benchmarks.
Mistral: Mistral Nemo is the lower-cost option to compare first when you want a similar workflow fit with less token spend.
GLM-5.2 is the better pick when response time matters more than maximum depth or premium quality.
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