GLM-5.3 Flash wins on price ($0.15 vs $1.4/1M input). GLM-5.3 wins on coding (91 vs 82). For most workflows, GLM-5.3 Flash is the stronger default — native vision and video, mit weights, fifteen cents per million.
The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.
GLM-5.3 Flash is the safest overall answer here when you want the strongest default instead of the lowest list price.
Google: Gemini 2.0 Flash is the lower-cost option to start with when you still need useful output at scale.
GLM-5.3 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 82 for GLM-5.3 Flash.
GLM-5.3 Flash is cheaper at $0.15/1M input tokens vs $1.4/1M for GLM-5.3.
GLM-5.3 Flash is the stronger default for budget tasks.
Go with GLM-5.3 Flash if you want one model to handle budget and multimodal — it targets cheap multimodal work at scale on MIT-licensed weights.
Switch to GLM-5.3 when your work is mostly agentic engineering and security work on open weights; on that narrower brief it is the better tool.
Both models serve different primary workflows — GLM-5.3 Flash for cheap multimodal work at scale on MIT-licensed weights, GLM-5.3 for agentic engineering and security work on open weights — 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
Native vision and video, MIT weights, fifteen cents per million.
Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.
You need top-tier reasoning or a published SWE-bench Verified figure — this is a volume model, not a ceiling model.
The fastest way to see where the recommendation shifts when your priority changes.
Native vision and video, MIT weights, fifteen cents per million.
Same price as GLM-5.2, far stronger on agents and security.
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-5.3 FlashZ.ai | $0.15/1M | $0.50/1M | $2.50 | 1M tokens | Fast | 82 | 76 | 78 |
| GLM-5.3Z.ai | $1.40/1M | $4.40/1M | $23 | 1M tokens | Balanced | 91 | 79 | 82 |
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.
A 320B-A18B mixture-of-experts model with native vision and video, MIT-licensed weights and a 1M context — at fifteen cents per million input tokens.
You need top-tier reasoning or a published SWE-bench Verified figure — this is a volume model, not a ceiling model.
The cheapest genuinely multimodal 1M-context model worth using in August 2026. If you are running vision or video at volume and can host weights, nothing at this price is close.
Released August 26, 2026. 320B total parameters, 18B active (320B-A18B MoE). Z.ai lists $0.15/1M input, $0.03/1M cached input and $0.50/1M output, with a launch promotion halving those rates through September 9, 2026. Self-reported against GLM-5.2: DeepSWE 63.4 vs 46.2, AutomationBench 48.8 vs 26.2.
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.
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GLM-5.3 Flash wins on more of the categories we score — budget, multimodal, coding — so it is the better default of the two. GLM-5.3 is the better pick when your work is mostly agentic engineering and security work on open weights. Neither is universally "better": GLM-5.3 Flash is aimed at cheap multimodal work at scale on MIT-licensed weights, GLM-5.3 at agentic engineering and security work on open weights.
GLM-5.3 Flash is cheaper at $0.15/1M input and $0.5/1M output. GLM-5.3 costs $1.4/1M input and $4.4/1M output.
Both GLM-5.3 Flash and GLM-5.3 have the same 1M context window.
GLM-5.3 is better for coding with a score of 91 vs GLM-5.3 Flash's 82 (out of 100). Claude Fable 5 is the overall coding leader in this directory at 100/100.
GLM-5.3 Flash is faster with a fast speed rating (score: 4) vs GLM-5.3's balanced rating (score: 3). Speed matters most for interactive and high-throughput work; for batch jobs the GLM-5.3 latency penalty is usually invisible.
No published SWE-bench Verified score. The launch promotion halves these rates only through September 9, 2026 — the $0.15/$0.50 list price applies after that. Avoid it if you need top-tier reasoning or a published SWE-bench Verified figure — this is a volume model, not a ceiling model. That is the main case for looking at GLM-5.3 instead.
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. Against GLM-5.3 Flash specifically, the gap shows up most on coding (82 vs 91).
Take a moderate workload of 10M input and 2M output tokens a month. GLM-5.3 Flash runs $2.50 (at $0.15/1M in and $0.5/1M out); GLM-5.3 runs $22.80 (at $1.4/1M in and $4.4/1M out). That is a $20.30/month difference — GLM-5.3 Flash is the cheaper of the two at this volume, and the gap scales linearly as you send more. 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 Flash for cheap multimodal work at scale on MIT-licensed weights, with GLM-5.3 handling agentic engineering and security work on open weights. Since GLM-5.3 Flash is both the stronger and the cheaper option here, a split mainly makes sense if GLM-5.3 covers a capability you specifically need.