GLM-5.3 wins on coding (91 vs 90). For most workflows, GLM-5.3 is the stronger default — same price as glm-5.2, far stronger on agents and security.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
GLM-5.3 is the safest overall answer here when you want the strongest default instead of the lowest list price.
Mistral: Mistral Nemo is the lower-cost option to start with when you still need useful output at scale.
GLM-5.2 is the better pick when response speed matters more than maximum reasoning depth.
GLM-5.3 leads on coding with a score of 91 vs 90 for GLM-5.2.
Both models are similarly priced — the decision comes down to capability, not cost.
GLM-5.3 is the stronger default for coding tasks.
Choose GLM-5.3 for agentic engineering and security work on open weights. Its coding and reasoning scores are what carry the recommendation here.
GLM-5.2 earns its place when your work is mostly budget agentic coding at scale, even though it loses the overall count here.
Both models serve different primary workflows — GLM-5.3 for agentic engineering and security work on open weights, GLM-5.2 for budget agentic coding at scale — so running each where it has a clear edge often beats forcing one to do both.
Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.
Z.ai / Budget / Aug 27, 2026
Same price as GLM-5.2, far stronger on agents and security.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
Your procurement process requires a SWE-bench Verified figure, or you need the closed-frontier reasoning ceiling.
The fastest way to see where the recommendation shifts when your priority changes.
Same price as GLM-5.2, far stronger on agents and security.
Top open-weights coder — beats GPT-5.5 at a sixth of the cost.
Every figure below is the provider's list price or a published capability score — the same numbers the recommendation on this page is built from.
| Model | Input | Output | Est. month | Context | Speed | Coding | Writing | Research |
|---|---|---|---|---|---|---|---|---|
| GLM-5.3Z.ai | $1.40/1M | $4.40/1M | $23 | 1M tokens | Balanced | 91 | 79 | 82 |
| GLM-5.2Z.ai | $1.40/1M | $4.40/1M | $23 | 1M tokens | Balanced | 90 | 78 | 80 |
Capability scores are out of 100 and reflect our own weighting of published benchmarks and production signals — see how we evaluate models. “Est. month” assumes 10M input and 2M output tokens at list price, with no batch or caching discounts applied, so treat it as a ceiling.
What each one is genuinely good at, where it falls down, and the situations we would steer you away from it — not just the headline score.
Z.ai's newest flagship, aimed squarely at software engineering, autonomous agents and cybersecurity — and the first open-weights model to beat Claude Mythos 5 on a security benchmark.
Your procurement process requires a SWE-bench Verified figure, or you need the closed-frontier reasoning ceiling.
The clear upgrade over GLM-5.2 at the same price — take it unless you specifically need a published SWE-bench Verified number to sign off on. The security benchmark lead over Mythos 5 is the genuinely new thing here.
Released August 14, 2026. Z.ai list pricing is $1.40/$4.40, the same rate as GLM-5.2; resellers discount from that list. Also available through the GLM Coding Plan from $18/mo. Reported GPQA Diamond 91.7% and Artificial Analysis Intelligence Index 59.5.
Z.ai's MIT-licensed open-weight flagship — the top open-weights coding model of mid-2026, beating GPT-5.5 on agentic coding benchmarks at roughly a sixth of the cost.
You need frontier reasoning ceiling or launch-day verified benchmarks.
The open-weights coding value king of mid-2026 — GPT-5.5-beating agentic coding at a fraction of the price, with an MIT license. DeepSeek V4-Flash undercuts it on price; GLM-5.2 answers with higher ceiling and two reasoning-effort modes.
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.
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GLM-5.3 wins on more of the categories we score — coding, reasoning, budget — so it is the better default of the two. GLM-5.2 is the better pick when your work is mostly budget agentic coding at scale. Neither is universally "better": GLM-5.3 is aimed at agentic engineering and security work on open weights, GLM-5.2 at budget agentic coding at scale.
Both models are similarly priced at $1.4/1M input tokens. The decision should come down to capability, not cost.
Both GLM-5.3 and GLM-5.2 have the same 1M context window.
GLM-5.3 is better for coding with a score of 91 vs GLM-5.2's 90 (out of 100). Claude Fable 5 is the overall coding leader in this directory at 100/100.
Both GLM-5.3 and GLM-5.2 have similar speed profiles — rated balanced. Neither will be the bottleneck if latency is your deciding factor.
No published SWE-bench Verified score, so it is absent from the benchmark most buyers compare on. Priced identically to GLM-5.2 at $1.40/$4.40 — the upgrade is capability, not value. Avoid it if your procurement process requires a SWE-bench Verified figure, or you need the closed-frontier reasoning ceiling. That is the main case for looking at GLM-5.2 instead.
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. Avoid it if you need frontier reasoning ceiling or launch-day verified benchmarks. Against GLM-5.3 specifically, the gap shows up most on coding (91 vs 90).
Take a moderate workload of 10M input and 2M output tokens a month. GLM-5.3 runs $22.80 (at $1.4/1M in and $4.4/1M out); GLM-5.2 runs $22.80 (at $1.4/1M in and $4.4/1M out). The gap is small enough that price should not decide this one. Output tokens dominate the bill on both, so prompt length matters far less than response length.
Yes, and for most teams that beats picking one. A common split is GLM-5.3 for agentic engineering and security work on open weights, with GLM-5.2 handling budget agentic coding at scale. Since GLM-5.3 is both the stronger and the cheaper option here, a split mainly makes sense if GLM-5.2 covers a capability you specifically need.