Pick GLM 5.2 for long-horizon agentic coding or project-level software engineering. 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 5.2 if you need self-hosting or data privacy; Qwen 3.7 Max if you want a managed API.
GLM 5.2 (Z.ai) and Qwen 3.7 Max (Alibaba) are two of the models people most often weigh against each other in 2026. GLM 5.2 is an open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: GLM 5.2 is about 1.8× cheaper on input ($1.4/$4.4 per 1M tokens vs $2.5/$7.5 per 1M tokens) — modest, but it adds up at steady volume.
Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Recency: GLM 5.2 is the newer model by about 24 days (released June 13, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GLM 5.2
Qwen 3.7 Max
Provider
Z.ai (China)
Alibaba (China)
Released
June 13, 2026
May 20, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$1.4/$4.4 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
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon agentic coding: GLM 5.2 — A core design strength of GLM 5.2.
Project-level software engineering: GLM 5.2 — A core design strength of GLM 5.2.
Tool use across long-running tasks: GLM 5.2 — A core design strength of GLM 5.2.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7): Qwen 3.7 Max — A core design strength of Qwen 3.7 Max.
1M-token long-document and full-codebase analysis: Qwen 3.7 Max — A core design strength of Qwen 3.7 Max.
MCP tool orchestration and multi-hour autonomous runs: Qwen 3.7 Max — A core design strength of Qwen 3.7 Max.
Lowest cost at scale: GLM 5.2 — At $1.4/$4.4 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: GLM 5.2 — At $1.4/$4.4 per 1M tokens it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs: GLM 5.2 — Open weights let you run it on your own hardware; Qwen 3.7 Max is API-only.
Anyone whose priority is long-horizon agentic coding: GLM 5.2 — 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 5.2: where it fits
An open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Released June 13, 2026 by Z.ai, it is built for long-horizon agentic coding, project-level software engineering, tool use across long-running tasks, and tops the open-weight intelligence index (SWE-bench Pro 62.1).
Its trade-offs are real: text-only — no native multimodal input, and new release with a limited third-party track record. At $1.4 in / $4.4 out per million tokens, it sits in the mid 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 5.2 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.
Frequently asked questions
Is GLM 5.2 or Qwen 3.7 Max better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5.2 leans toward long-horizon agentic coding 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 5.2 or Qwen 3.7 Max?
GLM 5.2 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GLM 5.2 and Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you GLM 5.2, 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 5.2 or Qwen 3.7 Max?
GLM 5.2 — released June 13, 2026, about 24 days after Qwen 3.7 Max.
GLM 5.2 vs Qwen 3.7 Max
Z.ai · China | Alibaba · China · Updated June 2026
Quick verdict
Pick GLM 5.2 for long-horizon agentic coding or project-level software engineering. 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 5.2 if you need self-hosting or data privacy; Qwen 3.7 Max if you want a managed API.
GLM 5.2 (Z.ai) and Qwen 3.7 Max (Alibaba) are two of the models people most often weigh against each other in 2026. GLM 5.2 is an open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GLM 5.2 is about 1.8× cheaper on input ($1.4/$4.4 per 1M tokens vs $2.5/$7.5 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
▸Recency: GLM 5.2 is the newer model by about 24 days (released June 13, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GLM 5.2
Qwen 3.7 Max
Provider
Z.ai (China)
Alibaba (China)
Released
June 13, 2026
May 20, 2026
Context window
1M (~1,500 pages)
1M (~1,500 pages)
Price (in/out)
$1.4/$4.4 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
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Long-horizon agentic coding
GLM 5.2
A core design strength of GLM 5.2.
Project-level software engineering
GLM 5.2
A core design strength of GLM 5.2.
Tool use across long-running tasks
GLM 5.2
A core design strength of GLM 5.2.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7)
Qwen 3.7 Max
A core design strength of Qwen 3.7 Max.
1M-token long-document and full-codebase analysis
Qwen 3.7 Max
A core design strength of Qwen 3.7 Max.
MCP tool orchestration and multi-hour autonomous runs
Qwen 3.7 Max
A core design strength of Qwen 3.7 Max.
Lowest cost at scale
GLM 5.2
At $1.4/$4.4 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GLM 5.2
At $1.4/$4.4 per 1M tokens it undercuts Qwen 3.7 Max, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ GLM 5.2
Open weights let you run it on your own hardware; Qwen 3.7 Max is API-only.
Anyone whose priority is long-horizon agentic coding
→ GLM 5.2
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 5.2: where it fits
An open-weight reasoning model built for long-horizon coding and multi-step agent workflows — strong and cheap. Released June 13, 2026 by Z.ai, it is built for long-horizon agentic coding, project-level software engineering, tool use across long-running tasks, and tops the open-weight intelligence index (SWE-bench Pro 62.1).
Its trade-offs are real: text-only — no native multimodal input, and new release with a limited third-party track record. At $1.4 in / $4.4 out per million tokens, it sits in the mid 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 5.2 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 5.2 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.
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GLM 5.2 leans toward long-horizon agentic coding 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 5.2 or Qwen 3.7 Max?
GLM 5.2 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?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both GLM 5.2 and Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you GLM 5.2, 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 5.2 or Qwen 3.7 Max?
GLM 5.2 — released June 13, 2026, about 24 days after Qwen 3.7 Max.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.