Z.ai prices GLM-5.3 API access at $1.40/1M input tokens and $4.40/1M output tokens, unchanged from GLM-5.2; Kimi K3 costs $3/1M input and $15/1M output tokens
Z.ai’s GLM-5.3 arrives after an earlier GLM-5.1 price increase and with a measured quality step: related coverage puts it seven points above GLM-5.2 and level with Kimi K3 on the same index. Holding the GLM-5.2 API rate therefore makes the release a performance-per-dollar move, not simply a new-model launch.
First-order effects
API buyers can access GLM-5.3’s higher reported score without paying more than they did for GLM-5.2.
Kimi K3 now faces a directly comparable model with the same reported index score but lower listed input and output token prices from Z.ai.
Second-order effects
For workloads that consume substantial output tokens, the listed price gap gives developers a concrete reason to benchmark GLM-5.3 against Kimi K3 on their reported score parity and task performance rather than select by model reputation alone.
Kimi’s pricing becomes more exposed where customers treat token spend as a core operating cost, while Z.ai must demonstrate that its benchmark gain translates into usable results.
Third-order effects
If model upgrades continue to arrive at unchanged API rates, frontier competition will increasingly center on effective cost per useful task rather than nominal token pricing alone.
The pattern points to model vendors absorbing more of the cost of capability improvements to win application workloads, putting sustained pressure on inference margins.
The trend: Comparable model quality is becoming a pricing contest in which vendors use stable or lower inference rates to turn benchmark gains into developer adoption.
#SlowHorses is one of the rarest and finest examples of scripted television: A procedural based on an airport novel series that cranks out its annual seasons like clockwork and boasts a crackerjack cast. https://www.avclub.com/...
And GLM-5.3 scores 60 on the Artificial Intelligence Index with 753B parameters. Developers also told us GLM-5.3 feels even stronger in complex, real-world workflows with cleaner code and less hallucination. Really grateful for all the feedbacks from the community in the
It really is ingenious how they're seemingly bringing Louisa Guy back into the fold. She's on the list just like everyone else. Ex-slow horses or otherwise, this concerns everyone. My God, Rosalind looks so fine this season.
it's crazy to me how olivia's treated like an evil witch in the hotd fandom but over in the slow horses fandom she's like the darling angel and universally adored 😭
No benchmark is more convincing than trying it yourself. Next, we're beginning a broader review of the model weights as we work toward a responsible open-weight release.
Until recently, raw model capability was the main benchmark. Now that prices are getting crazy high, the single most important metric is cost per task. Cost efficiency is only going to get way more attention from here on out.
GLM-5.3 API is now live. - Built for coding, defensive cybersecurity, and long-horizon agentic tasks - Priced the same as GLM-5.2 - Available via the official API and partner model gateways Get started: https://docs.z.ai/...
The WSJ has a negative anti-OpenAI bias for some time now even as the startup gains a ton of traction with its latest agentic coding models. If a fact doesn't fit their negative narrative, they don't publish it. It's bizarre. Example: Why hasn't the WSJ reported the 20%
Guys idk, open models in 2026 look pretty damn serious to me. Kimi K3: 60 GLM-5.3: 60 GPT-5.6 Sol: 61 @elonmusk could do the funniest thing by dropping Grok's weights.
GLM 5.3 as good as KIMI and better than Qwen3.8 2.4T. Do we really need trillions of parameters? or would a GLM with 2T+ parameters perform even better?
I've switched to GLM-5.3 for most of my SWE w/ K3 for remaining hard stuff. DSV4-Flash for volume work. Zai did quite well match K3 here in overall intelligence & likely exceeding it on CyberSecurity & SWE w/ just post training. Can't wait to see their next scale up.
GLM-5.3 scores 60 on the Artificial Analysis Intelligence Index. While GLM is best known for its coding capabilities, its strengths extend far beyond coding. GLM-5.3 delivers significant improvements in reasoning, general chat, and specialized domains such as law and finance.
GLM-5.3 from @Zai_org is live on OpenRouter! The same base model as GLM-5.2, with gains entirely from post-training: Terminal-Bench 3.0 jumps from 4.6 to 28.3, and DeepSWE v1.1 from 46.2 to 66.9. Use it now: https://openrouter.ai/...
Phenomenal But, as great as it is, they are overfocusing on SWE a little. Slight regression on CritPt. Kimi K3 is still the holistically strongest Chinese model.
BREAKING: GLM-5.3 by @Zai_org places 3rd overall on Design Arena with an Elo of 1351. This is a 6-position improvement from GLM-5.2, and makes GLM-5.3 the 2nd-highest-ranked open-weight model on real-world design tasks. Congratulations to the team on the launch!
I think GLM-5.3 is fine. I also think it might be overcooked. It talks like Opus 5 and that is a bad thing. I also have had more off-task sessions with it as my top orchestrator than 5.2. — My working assumption is that as a reviewer and a planning oracle it is very substitu…
AA's numbers are generally pretty well matched to the relative vibes, except that they really overrate frontier midrange models (Terra, Sonnet) — They do not include tests for long-haul directional adherence, though, which is a major gap — You will not notice in practice a 5-…
Z.ai's GLM-5.3 scores 60 on the Artificial Analysis Intelligence Index, seven points above GLM-5.2, on par with Kimi K3, but below Opus 5's 63 and Fable 5's 62