GLM 5 vs Qwen 3.7 Max
Z.ai · China | Alibaba · China · Updated June 2026
Quick verdict
Pick GLM 5 for agentic planning and long-horizon coding workflows or complex systems design and backend reasoning. Pick Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. Choose GLM 5 if you need self-hosting or data privacy; Qwen 3.7 Max if you want a managed API.
GLM 5 (Z.ai) and Qwen 3.7 Max (Alibaba) are two of the models people most often weigh against each other in 2026. GLM 5 is z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: GLM 5 is about 2.5× cheaper on input ($1/$3.2 per 1M tokens vs $2.5/$7.5 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: Qwen 3.7 Max holds 5× more — 1M (~1,500 pages) vs 200K (~300 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Qwen 3.7 Max is the newer model by about 3 months (released May 20, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | GLM 5 | Qwen 3.7 Max |
|---|---|---|
| Provider | Z.ai (China) | Alibaba (China) |
| Released | February 12, 2026 | May 20, 2026 |
| Context window | 200K (~300 pages) | 1M (~1,500 pages) |
| Price (in/out) | $1/$3.2 per 1M tokens | $2.5/$7.5 per 1M tokens |
| Open weight? | Yes — self-hostable | No — API only |
| Modalities | text, code | text, code |
| SWE-Bench Verified | 77.8% | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Agentic planning and long-horizon coding workflows
GLM 5
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding — and it runs cheaper at $1/$3.2 per 1M tokens.
Complex systems design and backend reasoning
GLM 5
Qwen 3.7 Max is comparatively weak here — trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning
Iterative self-correction on autonomous tasks
GLM 5
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding — and its weights are open while Qwen 3.7 Max is API-only.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7)
Qwen 3.7 Max
Its 1M window holds about 5× more than GLM 5's 200K in a single prompt.
1M-token long-document and full-codebase analysis
Qwen 3.7 Max
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships — and it carries the larger 1M context.
MCP tool orchestration and multi-hour autonomous runs
Qwen 3.7 Max
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships — and it is the newer of the two.
Lowest cost at scale
GLM 5
At $1/$3.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Qwen 3.7 Max
Its 1M window is about 5× larger than GLM 5's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GLM 5
At $1/$3.2 per 1M tokens it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Qwen 3.7 Max
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 5
Open weights let you run it on your own hardware; Qwen 3.7 Max is API-only.
Anyone whose priority is agentic planning and long-horizon coding workflows
→ GLM 5
It is specifically built for that.
Anyone whose priority is long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7)
→ Qwen 3.7 Max
That is its strongest area.
GLM 5: where it fits
Z.ai's flagship open-weight (MIT) MoE foundation model, engineered for complex systems design and long-horizon agentic coding. Released February 12, 2026 by Z.ai, it is built for agentic planning and long-horizon coding workflows, complex systems design and backend reasoning, iterative self-correction on autonomous tasks, and open weights under the permissive MIT license.
Its trade-offs are real: 200K context trails 1M-context rivals, and quickly superseded by GLM-5.1 and GLM-5.2. At $1 in / $3.2 out per million tokens, it sits in the budget price band.
Qwen 3.7 Max: where it fits
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.
Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 5 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Qwen 3.7 Max gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both GLM 5 and Qwen 3.7 Max without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is GLM 5 or Qwen 3.7 Max better for coding?
Public SWE-Bench figures are not available for Qwen 3.7 Max, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5 leans toward agentic planning and long-horizon coding workflows while Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GLM 5 or Qwen 3.7 Max?
GLM 5 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.7 Max is API-metered at $2.5/$7.5 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Qwen 3.7 Max — 1M vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 5 and Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you GLM 5, Qwen 3.7 Max and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, GLM 5 or Qwen 3.7 Max?
Qwen 3.7 Max — released May 20, 2026, about 3 months after GLM 5.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.