Z.ai launches GLM-5, its flagship open-weight model, saying it has best-in-class performance among open-source models in reasoning, coding, and agentic tasks
We are launching GLM-5, targeting complex systems engineering and long-horizon agentic tasks. Scaling is still one of the most important ways …
Z.ai
Context & Ripple Effects
GLM-5 extends Z.ai’s open-weight model line after GLM-4.6’s coding and reasoning positioning. The launch shifts the company’s stated focus toward complex systems engineering and long-horizon agentic work, where model capability must translate into sustained task execution.
The announcement also begins a fast iteration cycle: later coverage records GLM-5.1’s larger model release and benchmark claims and GLM-5.2 improvements for agentic coding. That sequence makes GLM-5 a meaningful product-positioning marker, though its performance claims remain Z.ai’s own.
First-order effects
Z.ai gains a new flagship open-weight offering positioned around reasoning, coding, and agentic tasks, giving developers another model to assess for complex engineering workloads.
Teams already evaluating open-weight models can add GLM-5 to their testing set, but will need to validate Z.ai’s best-in-class claim against their own tasks and deployment constraints.
Second-order effects
Other open-weight model providers face more pressure to compete on agentic coding and long-horizon execution, not just broad benchmark performance.
Enterprise model selection becomes more workload-specific: procurement teams are pushed to compare models on systems-engineering and agentic-task evaluations rather than treating “open source” as a single capability tier.
Third-order effects
If rapid GLM-5-family releases continue, open-weight competition may increasingly turn on iteration speed and demonstrated workflow performance, narrowing the distinction between open and proprietary options for some development use cases.
The durable advantage may shift from a model’s headline ranking to the evaluation, integration, and operational discipline required to deploy it reliably in multi-step workflows.
The trend: This is one data point in the industrialization of open-weight AI, as vendors target higher-value coding and agentic workflows through rapid model iteration.
Introducing GLM-5: From Vibe Coding to Agentic Engineering GLM-5 is built for complex systems engineering and long-horizon agentic tasks. Compared to GLM-4.5, it scales from 355B params (32B active) to 744B (40B active), with pre-training data growing from 23T to 28.5T tokens. [i…
Technical report for GLM 5 is out, it looks really good! Looks nearly as good as Opus 4.5, actually. It's much larger than GLM 4.7 though, at 774B total 40B active https://z.ai/... [image]
The recent release of Seedance v2.0 and GLM-5 shows why slowing down is not an option for the US. China is hot on the US's heels, and giving up is not an option. Therefore, the storm will only intensify and accelerate.
GLM-5 is now on AI Gateway. Better long-range planning, multiple thinking modes, and improved multi-step agent tasks versus previous https://z.ai/ models. Use 𝚖𝚘𝚍𝚎𝚕: ‘𝚣𝚊𝚒/𝚐𝚕𝚖-𝟻’ to get started. https://vercel.com/...
glm 5 looks insane basically opus 4.5 and gpt-5.2 level benchmarks while 10x cheaper than opus 4.5 these open source models are saving our wallets fr [image]
GLM 5 just dropped and the pricing is absurd. $0.80 per million input tokens. $2.56 per million output tokens. For context: Claude Opus 4.6: $5/$25 GPT 5.3 Codex: $1.75/$14 GLM-5: $0.80/$2.56 GLM 5 is 6x cheaper than Opus on input and 10x cheaper on output. 200K context [image]
I've been testing GLM-5 over the last couple of days. Its reasoning is really good; - decomposes the challenging problem correctly - identifies the right failure modes - arrives at a valid architectural solution GLM-5 also does something interesting where it compresses concepts […
This is a HUGE win for developers. Claude Code is excellent, but the $200/mo Max plan can be expensive for daily use. GLM-5 works inside Claude Code, with (arguably) comparable performance at ~1/3 the cost. Setup takes ~1 minute: • Install Claude Code as usual • Run 'npx
I wish @Zai_org had more compute. The GLM models are so good, but their throughput over the coding plan is pretty frustrating. I'm hoping that changes soon. Things are looking better than ever for open-weight models with the recent Kimi and GLM launches.
On Vending Bench 2, GLM-5 ranks #1 among open-source models, finishing with a final account balance of $4,432. It approaches Claude Opus 4.5, demonstrating strong long-term planning and resource management. [image]
i felt agentic engineering era is coming claude opus 4.6 and gpt-5.3 codex got me thinking coding models have entered a new era. they're literally building systems. looking ahead to 2026, imo LLMs will go beyond generating text, and start executing tasks end to end. our team
GLM-5 is out, amazing release with very very good benchmark scores even on tasks like @andonlabs vending bench 2 i think one of the most crazy parts of this is that the RL framework that they use is open (based on megatron for training, @sgl_project for inference), it's somewhat …
A new open-source model has entered the Arena. Come check out @Zai_org's latest GLM-5 in Text and Code. Test out its coding chops in Text and its agentic coding capabilities in Code. Battle with the top frontier models and don't forget to vote - scores coming soon. [image]
For GLM Coding Plan subscribers: Due to limited compute capacity, we're rolling out GLM-5 to Coding Plan users gradually. - Max plan users: You can enable GLM-5 now by updating the model name to “GLM-5” (e.g. in ~/.claude/settings.json for Claude Code). - Other plan tiers:
Congratulations to @jietang @ZixuanLi_ and the entire @Zai_org team on the GLM 5 release: based on >6K votes, it's the best open-weight model on the @yupp_ai leaderboard (with speed control)!
🎉 The mysterious Pony Alpha is finally revealed, congrats to @Zai_org on releasing GLM-5! SGLang is ready to support on day-0. 🛠️ 744B params (40B active) model built for complex systems engineering & long-horizon agentic tasks 📚 28.5T tokens pretraining for a stronger [image]
On our internal evaluation suite CC-Bench-V2, GLM-5 significantly outperforms GLM-4.7 across frontend, backend, and long-horizon tasks, narrowing the gap with Claude Opus 4.5. [image]