Pick GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions or strong agentic coding for the price — 73.8% on swe-bench verified undercut most closed frontier models at launch. Pick Qwen 3.6 Plus for strong gpqa diamond science reasoning or open-weight and budget-friendly. Choose GLM 4.7 if you need self-hosting or data privacy; Qwen 3.6 Plus if you want a managed API.
GLM 4.7 (Z.ai) and Qwen 3.6 Plus (Alibaba) are two of the models people most often weigh against each other in 2026. GLM 4.7 is an MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Qwen 3.6 Plus is alibaba's open-weight contender — surprising benchmark wins at a budget price. They diverge most on price, context window, open vs. closed weights and coding benchmarks — each quantified below from the models' real specs.
Key differences
Price: Qwen 3.6 Plus is about 1.8× cheaper on input ($0.325/$1.95 per 1M tokens vs $0.6/$2.2 per 1M tokens) — modest, but it adds up at steady volume.
Context window: Qwen 3.6 Plus holds 4.9× more — 1M (~1,500 pages) vs 200K (~304 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Coding: Qwen 3.6 Plus leads SWE-Bench Verified by 5.0 points (73.8% vs 78.8%) — a real edge on hard, real-world software tasks.
Recency: Qwen 3.6 Plus is the newer model by about 3 months (released March 31, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GLM 4.7
Qwen 3.6 Plus
Provider
Z.ai (China)
Alibaba (China)
Released
December 22, 2025
March 31, 2026
Context window
200K (~304 pages)
1M (~1,500 pages)
Price (in/out)
$0.6/$2.2 per 1M tokens
$0.325/$1.95 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, code
SWE-Bench Verified
73.8%
78.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions: GLM 4.7 — Open weights make this possible at all — Qwen 3.6 Plus is API-only, so it cannot leave the vendor's servers.
Strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch: GLM 4.7 — Qwen 3.6 Plus is comparatively weak here — benchmark coverage still maturing
An unusually generous 128K maximum output, which suits bulk refactors and long generation: GLM 4.7 — An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and its weights are open while Qwen 3.6 Plus is API-only.
Strong GPQA Diamond science reasoning: Qwen 3.6 Plus — Alibaba's open-weight contender — surprising benchmark wins at a budget price — and it leads SWE-Bench Verified 78.8% to 73.8%.
Open-weight and budget-friendly: Qwen 3.6 Plus — At $0.325/$1.95 per 1M tokens it undercuts GLM 4.7 ($0.6/$2.2 per 1M tokens), and that gap compounds at volume.
1M context: Qwen 3.6 Plus — Its 1M window holds about 4.9× more than GLM 4.7's 200K in a single prompt.
Lowest cost at scale: Qwen 3.6 Plus — At $0.325/$1.95 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Qwen 3.6 Plus — Its 1M window is about 4.9× larger than GLM 4.7's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Qwen 3.6 Plus — At $0.325/$1.95 per 1M tokens it undercuts GLM 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Qwen 3.6 Plus — Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs: GLM 4.7 — Open weights let you run it on your own hardware; Qwen 3.6 Plus is API-only.
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions: GLM 4.7 — It is specifically built for that.
Anyone whose priority is strong gpqa diamond science reasoning: Qwen 3.6 Plus — That is its strongest area.
GLM 4.7: where it fits
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Released December 22, 2025 by Z.ai, it is built for genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions, strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch, an unusually generous 128K maximum output, which suits bulk refactors and long generation, and cheap long-running agent loops thanks to aggressive prompt caching.
Its trade-offs are real: two generations behind — GLM 5, 5.1 and 5.2 have all shipped since, and new builds should default to those, its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro, and text-only with no vision, and self-hosting a 358B model is a serious hardware commitment. At $0.6 in / $2.2 out per million tokens, it sits in the budget price band.
Qwen 3.6 Plus: where it fits
Alibaba's open-weight contender — surprising benchmark wins at a budget price. Released March 31, 2026 by Alibaba, it is built for strong GPQA Diamond science reasoning, open-weight and budget-friendly, 1M context, and multilingual coverage.
Its trade-offs: less Western ecosystem tooling, and benchmark coverage still maturing. At $0.325 in / $1.95 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 4.7 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Qwen 3.6 Plus 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 4.7 or Qwen 3.6 Plus better for coding?
On SWE-Bench Verified, GLM 4.7 scores 73.8% and Qwen 3.6 Plus scores 78.8% — Qwen 3.6 Plus has the measurable edge.
Which is cheaper, GLM 4.7 or Qwen 3.6 Plus?
GLM 4.7 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.6 Plus is API-metered at $0.325/$1.95 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 3.6 Plus — 1M vs 200K, about 4.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 4.7 and Qwen 3.6 Plus together?
Yes — a multi-model platform like LumiChats gives you GLM 4.7, Qwen 3.6 Plus 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 4.7 or Qwen 3.6 Plus?
Qwen 3.6 Plus — released March 31, 2026, about 3 months after GLM 4.7.
GLM 4.7 vs Qwen 3.6 Plus
Z.ai · China | Alibaba · China · Updated June 2026
Quick verdict
Pick GLM 4.7 for genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions or strong agentic coding for the price — 73.8% on swe-bench verified undercut most closed frontier models at launch. Pick Qwen 3.6 Plus for strong gpqa diamond science reasoning or open-weight and budget-friendly. Choose GLM 4.7 if you need self-hosting or data privacy; Qwen 3.6 Plus if you want a managed API.
GLM 4.7 (Z.ai) and Qwen 3.6 Plus (Alibaba) are two of the models people most often weigh against each other in 2026. GLM 4.7 is an MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Qwen 3.6 Plus is alibaba's open-weight contender — surprising benchmark wins at a budget price. They diverge most on price, context window, open vs. closed weights and coding benchmarks — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Qwen 3.6 Plus is about 1.8× cheaper on input ($0.325/$1.95 per 1M tokens vs $0.6/$2.2 per 1M tokens) — modest, but it adds up at steady volume.
▸Context window: Qwen 3.6 Plus holds 4.9× more — 1M (~1,500 pages) vs 200K (~304 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Coding: Qwen 3.6 Plus leads SWE-Bench Verified by 5.0 points (73.8% vs 78.8%) — a real edge on hard, real-world software tasks.
▸Recency: Qwen 3.6 Plus is the newer model by about 3 months (released March 31, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GLM 4.7
Qwen 3.6 Plus
Provider
Z.ai (China)
Alibaba (China)
Released
December 22, 2025
March 31, 2026
Context window
200K (~304 pages)
1M (~1,500 pages)
Price (in/out)
$0.6/$2.2 per 1M tokens
$0.325/$1.95 per 1M tokens
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, image, code
SWE-Bench Verified
73.8%
78.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions
GLM 4.7
Open weights make this possible at all — Qwen 3.6 Plus is API-only, so it cannot leave the vendor's servers.
Strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch
GLM 4.7
Qwen 3.6 Plus is comparatively weak here — benchmark coverage still maturing
An unusually generous 128K maximum output, which suits bulk refactors and long generation
GLM 4.7
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and its weights are open while Qwen 3.6 Plus is API-only.
Strong GPQA Diamond science reasoning
Qwen 3.6 Plus
Alibaba's open-weight contender — surprising benchmark wins at a budget price — and it leads SWE-Bench Verified 78.8% to 73.8%.
Open-weight and budget-friendly
Qwen 3.6 Plus
At $0.325/$1.95 per 1M tokens it undercuts GLM 4.7 ($0.6/$2.2 per 1M tokens), and that gap compounds at volume.
1M context
Qwen 3.6 Plus
Its 1M window holds about 4.9× more than GLM 4.7's 200K in a single prompt.
Lowest cost at scale
Qwen 3.6 Plus
At $0.325/$1.95 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Qwen 3.6 Plus
Its 1M window is about 4.9× larger than GLM 4.7's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Qwen 3.6 Plus
At $0.325/$1.95 per 1M tokens it undercuts GLM 4.7, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Qwen 3.6 Plus
Larger 1M window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 4.7
Open weights let you run it on your own hardware; Qwen 3.6 Plus is API-only.
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions
→ GLM 4.7
It is specifically built for that.
Anyone whose priority is strong gpqa diamond science reasoning
→ Qwen 3.6 Plus
That is its strongest area.
GLM 4.7: where it fits
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2. Released December 22, 2025 by Z.ai, it is built for genuinely permissive open weights — an MIT-licensed 358B mixture-of-experts with no commercial restrictions, strong agentic coding for the price — 73.8% on SWE-Bench Verified undercut most closed frontier models at launch, an unusually generous 128K maximum output, which suits bulk refactors and long generation, and cheap long-running agent loops thanks to aggressive prompt caching.
Its trade-offs are real: two generations behind — GLM 5, 5.1 and 5.2 have all shipped since, and new builds should default to those, its Verified lead narrows sharply on harder evaluations like SWE-Bench Pro, and text-only with no vision, and self-hosting a 358B model is a serious hardware commitment. At $0.6 in / $2.2 out per million tokens, it sits in the budget price band.
Qwen 3.6 Plus: where it fits
Alibaba's open-weight contender — surprising benchmark wins at a budget price. Released March 31, 2026 by Alibaba, it is built for strong GPQA Diamond science reasoning, open-weight and budget-friendly, 1M context, and multilingual coverage.
Its trade-offs: less Western ecosystem tooling, and benchmark coverage still maturing. At $0.325 in / $1.95 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
The defining split here is open vs. closed. GLM 4.7 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Qwen 3.6 Plus 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 4.7 and Qwen 3.6 Plus 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.
On SWE-Bench Verified, GLM 4.7 scores 73.8% and Qwen 3.6 Plus scores 78.8% — Qwen 3.6 Plus has the measurable edge.
Which is cheaper, GLM 4.7 or Qwen 3.6 Plus?
GLM 4.7 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Qwen 3.6 Plus is API-metered at $0.325/$1.95 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 3.6 Plus — 1M vs 200K, about 4.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GLM 4.7 and Qwen 3.6 Plus together?
Yes — a multi-model platform like LumiChats gives you GLM 4.7, Qwen 3.6 Plus 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 4.7 or Qwen 3.6 Plus?
Qwen 3.6 Plus — released March 31, 2026, about 3 months after GLM 4.7.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.