Pick Claude Fable 5 for the hardest reasoning and most complex problems or long-horizon, multi-step agentic work. 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 Fable 5 if you want a managed API.
Claude Fable 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 Fable 5 is anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: GLM 4.7 is about 17× cheaper on input ($0.6/$2.2 per 1M tokens vs $10/$50 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Claude Fable 5 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.
Recency: Claude Fable 5 is the newer model by about 6 months (released June 9, 2026), 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 Fable 5
GLM 4.7
Provider
Anthropic (US)
Z.ai (China)
Released
June 9, 2026
December 22, 2025
Context window
1M (~1,500 pages)
200K (~304 pages)
Price (in/out)
$10/$50 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
Not published
73.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
The hardest reasoning and most complex problems: Claude Fable 5 — Anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive — and it carries the larger 1M context.
Long-horizon, multi-step agentic work: Claude Fable 5 — Its 1M window holds about 4.9× more than GLM 4.7's 200K in a single prompt.
Frontier-level analysis and research: Claude Fable 5 — Anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive — and it is the newer of the two.
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 Fable 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 Fable 5 ($10/$50 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 — An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and it runs cheaper at $0.6/$2.2 per 1M tokens.
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.
Largest single-prompt input: Claude Fable 5 — 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: GLM 4.7 — At $0.6/$2.2 per 1M tokens it undercuts Claude Fable 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Claude Fable 5 — 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; Claude Fable 5 is API-only.
Anyone whose priority is the hardest reasoning and most complex problems: Claude Fable 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 Fable 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 Fable 5: where it fits
Anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive. Released June 9, 2026 by Anthropic, it is built for the hardest reasoning and most complex problems, long-horizon, multi-step agentic work, frontier-level analysis and research, and work where maximum capability outweighs cost.
Its trade-offs are real: highest price in the Claude lineup, and tier access was temporarily suspended in June 2026 under a US export-control directive. At $10 in / $50 out per million tokens, it sits in the premium 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 Fable 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 Fable 5 or GLM 4.7 better for coding?
Public SWE-Bench figures are not available for Claude Fable 5, so the honest test is your own repository — run an identical real bug through both. By design, Claude Fable 5 leans toward the hardest reasoning and most complex problems while GLM 4.7 leans toward genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Fable 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 Fable 5 is API-metered at $10/$50 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?
Claude Fable 5 — 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 Claude Fable 5 and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Claude Fable 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 Fable 5 or GLM 4.7?
Claude Fable 5 — released June 9, 2026, about 6 months after GLM 4.7.
Claude Fable 5 vs GLM 4.7
Anthropic · US | Z.ai · China · Updated June 2026
Quick verdict
Pick Claude Fable 5 for the hardest reasoning and most complex problems or long-horizon, multi-step agentic work. 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 Fable 5 if you want a managed API.
Claude Fable 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 Fable 5 is anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive. 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 and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Price: GLM 4.7 is about 17× cheaper on input ($0.6/$2.2 per 1M tokens vs $10/$50 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Claude Fable 5 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.
▸Recency: Claude Fable 5 is the newer model by about 6 months (released June 9, 2026), 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 Fable 5
GLM 4.7
Provider
Anthropic (US)
Z.ai (China)
Released
June 9, 2026
December 22, 2025
Context window
1M (~1,500 pages)
200K (~304 pages)
Price (in/out)
$10/$50 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
Not published
73.8%
MRCR v2 @ 1M
Not published
Not published
Who wins what
The hardest reasoning and most complex problems
Claude Fable 5
Anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive — and it carries the larger 1M context.
Long-horizon, multi-step agentic work
Claude Fable 5
Its 1M window holds about 4.9× more than GLM 4.7's 200K in a single prompt.
Frontier-level analysis and research
Claude Fable 5
Anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive — and it is the newer of the two.
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 Fable 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 Fable 5 ($10/$50 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
An MIT-licensed 358B open mixture-of-experts with strong 73.8% SWE-Bench Verified coding — but two generations behind GLM 5.2 — and it runs cheaper at $0.6/$2.2 per 1M tokens.
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.
Largest single-prompt input
Claude Fable 5
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
→ GLM 4.7
At $0.6/$2.2 per 1M tokens it undercuts Claude Fable 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Claude Fable 5
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; Claude Fable 5 is API-only.
Anyone whose priority is the hardest reasoning and most complex problems
→ Claude Fable 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 Fable 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 Fable 5: where it fits
Anthropic's top public Mythos-class model and its most capable yet, though tier access was temporarily suspended in June 2026 under a US export-control directive. Released June 9, 2026 by Anthropic, it is built for the hardest reasoning and most complex problems, long-horizon, multi-step agentic work, frontier-level analysis and research, and work where maximum capability outweighs cost.
Its trade-offs are real: highest price in the Claude lineup, and tier access was temporarily suspended in June 2026 under a US export-control directive. At $10 in / $50 out per million tokens, it sits in the premium 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 Fable 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 Fable 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.
Public SWE-Bench figures are not available for Claude Fable 5, so the honest test is your own repository — run an identical real bug through both. By design, Claude Fable 5 leans toward the hardest reasoning and most complex problems while GLM 4.7 leans toward genuinely permissive open weights — an mit-licensed 358b mixture-of-experts with no commercial restrictions, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Fable 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 Fable 5 is API-metered at $10/$50 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?
Claude Fable 5 — 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 Claude Fable 5 and GLM 4.7 together?
Yes — a multi-model platform like LumiChats gives you Claude Fable 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 Fable 5 or GLM 4.7?
Claude Fable 5 — released June 9, 2026, about 6 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.