Pick Claude Sonnet 4.5 for agentic coding — 77.2% on swe-bench verified, the best score any model had posted at its launch or computer use and gui automation (61.4% osworld at launch). 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. Choose GLM 4.7 if you need self-hosting or data privacy; Claude Sonnet 4.5 if you want a managed API.
Claude Sonnet 4.5 (Anthropic, US) and GLM 4.7 (Z.ai, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Claude Sonnet 4.5 is september 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded. 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. 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: GLM 4.7 is about 5× cheaper on input ($0.6/$2.2 per 1M tokens vs $3/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: 200K vs 200K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Coding: Claude Sonnet 4.5 leads SWE-Bench Verified by 3.4 points (77.2% vs 73.8%) — a real edge on hard, real-world software tasks.
Recency: GLM 4.7 is the newer model by about 3 months (released December 22, 2025), usually meaning fresher training data and capabilities.
Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Specifications
Spec
Claude Sonnet 4.5
GLM 4.7
Provider
Anthropic (US)
Z.ai (China)
Released
September 29, 2025
December 22, 2025
Context window
200K (~300 pages)
200K (~304 pages)
Price (in/out)
$3/$15 per 1M tokens
$0.6/$2.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
77.2%
73.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic coding — 77.2% on SWE-Bench Verified, the best score any model had posted at its launch: Claude Sonnet 4.5 — It scores 77.2% on SWE-Bench Verified against GLM 4.7's 73.8% — a 3.4-point edge on real repository work.
Computer use and GUI automation (61.4% OSWorld at launch): Claude Sonnet 4.5 — September 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded — and it leads SWE-Bench Verified 77.2% to 73.8%.
Long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks: Claude Sonnet 4.5 — Claude Sonnet 4.5 lists long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks among its strengths; GLM 4.7 does not.
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 — Claude Sonnet 4.5 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 — At $0.6/$2.2 per 1M tokens it undercuts Claude Sonnet 4.5 ($3/$15 per 1M tokens), and that gap compounds at volume.
An unusually generous 128K maximum output, which suits bulk refactors and long generation: GLM 4.7 — Claude Sonnet 4.5 is comparatively weak here — missing the modern API surface: no adaptive thinking, no effort control, and half the max output of newer Sonnets
Lowest cost at scale: GLM 4.7 — At $0.6/$2.2 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 4.7 — At $0.6/$2.2 per 1M tokens it undercuts Claude Sonnet 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GLM 4.7 — Larger 200K 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; Claude Sonnet 4.5 is API-only.
Anyone whose priority is agentic coding — 77.2% on swe-bench verified, the best score any model had posted at its launch: Claude Sonnet 4.5 — It is specifically built for that.
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions: GLM 4.7 — That is its strongest area.
An enterprise with regional data-residency rules: Claude Sonnet 4.5 or GLM 4.7 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Sonnet 4.5: where it fits
September 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded. Released September 29, 2025 by Anthropic, it is built for agentic coding — 77.2% on SWE-Bench Verified, the best score any model had posted at its launch, computer use and GUI automation (61.4% OSWorld at launch), long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks, and tracking its own remaining token budget natively, which few models do.
Its trade-offs are real: superseded twice — Sonnet 4.6 and Sonnet 5 match or beat it at the same or lower price, capped at 200K since Anthropic retired its 1M beta in April 2026, while its successors ship 1M as standard, and missing the modern API surface: no adaptive thinking, no effort control, and half the max output of newer Sonnets. At $3 in / $15 out per million tokens, it sits in the mid price band.
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: 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.
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. Claude Sonnet 4.5 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 Claude Sonnet 4.5 or GLM 4.7 better for coding?
On SWE-Bench Verified, Claude Sonnet 4.5 scores 77.2% and GLM 4.7 scores 73.8% — Claude Sonnet 4.5 has the measurable edge.
Which is cheaper, Claude Sonnet 4.5 or GLM 4.7?
GLM 4.7 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Sonnet 4.5 is API-metered at $3/$15 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?
Effectively neither — 200K vs 200K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Sonnet 4.5 and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Claude Sonnet 4.5, GLM 4.7 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, Claude Sonnet 4.5 or GLM 4.7?
GLM 4.7 — released December 22, 2025, about 3 months after Claude Sonnet 4.5.
Claude Sonnet 4.5 vs GLM 4.7
Anthropic · US | Z.ai · China · Updated June 2026
Quick verdict
Pick Claude Sonnet 4.5 for agentic coding — 77.2% on swe-bench verified, the best score any model had posted at its launch or computer use and gui automation (61.4% osworld at launch). 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. Choose GLM 4.7 if you need self-hosting or data privacy; Claude Sonnet 4.5 if you want a managed API.
Claude Sonnet 4.5 (Anthropic, US) and GLM 4.7 (Z.ai, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Claude Sonnet 4.5 is september 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded. 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. 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: GLM 4.7 is about 5× cheaper on input ($0.6/$2.2 per 1M tokens vs $3/$15 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: 200K vs 200K — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Coding: Claude Sonnet 4.5 leads SWE-Bench Verified by 3.4 points (77.2% vs 73.8%) — a real edge on hard, real-world software tasks.
▸Recency: GLM 4.7 is the newer model by about 3 months (released December 22, 2025), usually meaning fresher training data and capabilities.
▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
Spec
Claude Sonnet 4.5
GLM 4.7
Provider
Anthropic (US)
Z.ai (China)
Released
September 29, 2025
December 22, 2025
Context window
200K (~300 pages)
200K (~304 pages)
Price (in/out)
$3/$15 per 1M tokens
$0.6/$2.2 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image, code
text, code
SWE-Bench Verified
77.2%
73.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
Agentic coding — 77.2% on SWE-Bench Verified, the best score any model had posted at its launch
Claude Sonnet 4.5
It scores 77.2% on SWE-Bench Verified against GLM 4.7's 73.8% — a 3.4-point edge on real repository work.
Computer use and GUI automation (61.4% OSWorld at launch)
Claude Sonnet 4.5
September 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded — and it leads SWE-Bench Verified 77.2% to 73.8%.
Long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks
Claude Sonnet 4.5
Claude Sonnet 4.5 lists long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks among its strengths; GLM 4.7 does not.
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 — Claude Sonnet 4.5 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
At $0.6/$2.2 per 1M tokens it undercuts Claude Sonnet 4.5 ($3/$15 per 1M tokens), and that gap compounds at volume.
An unusually generous 128K maximum output, which suits bulk refactors and long generation
GLM 4.7
Claude Sonnet 4.5 is comparatively weak here — missing the modern API surface: no adaptive thinking, no effort control, and half the max output of newer Sonnets
Lowest cost at scale
GLM 4.7
At $0.6/$2.2 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 4.7
At $0.6/$2.2 per 1M tokens it undercuts Claude Sonnet 4.5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GLM 4.7
Larger 200K 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; Claude Sonnet 4.5 is API-only.
Anyone whose priority is agentic coding — 77.2% on swe-bench verified, the best score any model had posted at its launch
→ Claude Sonnet 4.5
It is specifically built for that.
Anyone whose priority is genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions
→ GLM 4.7
That is its strongest area.
An enterprise with regional data-residency rules
→ Claude Sonnet 4.5 or GLM 4.7
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Sonnet 4.5: where it fits
September 2025's coding state of the art at $3/$15 — still supported, but 200K-capped and twice superseded. Released September 29, 2025 by Anthropic, it is built for agentic coding — 77.2% on SWE-Bench Verified, the best score any model had posted at its launch, computer use and GUI automation (61.4% OSWorld at launch), long-horizon autonomy — Anthropic reported 30+ hours of sustained focus on multi-step tasks, and tracking its own remaining token budget natively, which few models do.
Its trade-offs are real: superseded twice — Sonnet 4.6 and Sonnet 5 match or beat it at the same or lower price, capped at 200K since Anthropic retired its 1M beta in April 2026, while its successors ship 1M as standard, and missing the modern API surface: no adaptive thinking, no effort control, and half the max output of newer Sonnets. At $3 in / $15 out per million tokens, it sits in the mid price band.
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: 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.
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. Claude Sonnet 4.5 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 Claude Sonnet 4.5 and GLM 4.7 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.
Is Claude Sonnet 4.5 or GLM 4.7 better for coding?
On SWE-Bench Verified, Claude Sonnet 4.5 scores 77.2% and GLM 4.7 scores 73.8% — Claude Sonnet 4.5 has the measurable edge.
Which is cheaper, Claude Sonnet 4.5 or GLM 4.7?
GLM 4.7 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Sonnet 4.5 is API-metered at $3/$15 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?
Effectively neither — 200K vs 200K is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Sonnet 4.5 and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Claude Sonnet 4.5, GLM 4.7 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, Claude Sonnet 4.5 or GLM 4.7?
GLM 4.7 — released December 22, 2025, about 3 months after Claude Sonnet 4.5.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.