Pick Claude Fable 5.1 for terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) or cursorbench 3.2 agentic coding (73.4%). Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Choose GLM 5.1 if you need self-hosting or data privacy; Claude Fable 5.1 if you want a managed API.
Claude Fable 5.1 (Anthropic, US) and GLM 5.1 (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 5.1 is anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. GLM 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Price: GLM 5.1 is about 7.1× cheaper on input ($1.4/$4.4 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 5.1 holds 5× more — 1M tokens (~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: Claude Fable 5.1 is the newer model by about 5 months (released September 1, 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 5.1
GLM 5.1
Provider
Anthropic (US)
Z.ai (China)
Released
September 1, 2026
April 7, 2026
Context window
1M tokens (~1,500 pages)
200K (~300 pages)
Price (in/out)
$10/$50 per 1M tokens
$1.4/$4.4 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%): Claude Fable 5.1 — Anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores — and it carries the larger 1M tokens context.
CursorBench 3.2 agentic coding (73.4%): Claude Fable 5.1 — Anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores — and it is the newer of the two.
Cache-read pricing cut to a quarter of other Claude models: Claude Fable 5.1 — Claude Fable 5.1 lists cache-read pricing cut to a quarter of other Claude models among its strengths; GLM 5.1 does not.
Long-horizon autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours — and it runs cheaper at $1.4/$4.4 per 1M tokens.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch): GLM 5.1 — Open weights make this possible at all — Claude Fable 5.1 is API-only, so it cannot leave the vendor's servers.
Sustained tool use across thousands of calls: GLM 5.1 — An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours — and its weights are open while Claude Fable 5.1 is API-only.
Lowest cost at scale: GLM 5.1 — At $1.4/$4.4 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 5.1 — Its 1M tokens window is about 5× larger than GLM 5.1's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GLM 5.1 — At $1.4/$4.4 per 1M tokens it undercuts Claude Fable 5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Claude Fable 5.1 — Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs: GLM 5.1 — Open weights let you run it on your own hardware; Claude Fable 5.1 is API-only.
Anyone whose priority is terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%): Claude Fable 5.1 — It is specifically built for that.
Anyone whose priority is long-horizon autonomous agentic engineering (up to 8-hour runs): GLM 5.1 — That is its strongest area.
An enterprise with regional data-residency rules: Claude Fable 5.1 or GLM 5.1 — Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Fable 5.1: where it fits
Anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. Released September 1, 2026 by Anthropic, it is built for terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%), cursorBench 3.2 agentic coding (73.4%), cache-read pricing cut to a quarter of other Claude models, and long, multistep, document-heavy professional work with 1M-token context.
Its trade-offs are real: anthropic has not published an official SWE-bench Verified score for this model, restricted Mythos 5.1 variant outscores it on some benchmarks due to lighter safeguards (Terminal-Bench 4.0: 60.9% vs 55.8%), and closed weights, no self-hosting option. At $10 in / $50 out per million tokens, it sits in the premium price band.
GLM 5.1: where it fits
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.
Its trade-offs: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 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 5.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Claude Fable 5.1 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 5.1 or GLM 5.1 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, Claude Fable 5.1 leans toward terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) while GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Fable 5.1 or GLM 5.1?
GLM 5.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Fable 5.1 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 5.1 — 1M tokens vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Fable 5.1 and GLM 5.1 together?
Yes — a multi-model platform like LumiChats gives you Claude Fable 5.1, GLM 5.1 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 5.1 or GLM 5.1?
Claude Fable 5.1 — released September 1, 2026, about 5 months after GLM 5.1.
Claude Fable 5.1 vs GLM 5.1
Anthropic · US | Z.ai · China · Updated June 2026
Quick verdict
Pick Claude Fable 5.1 for terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) or cursorbench 3.2 agentic coding (73.4%). Pick GLM 5.1 for long-horizon autonomous agentic engineering (up to 8-hour runs) or state-of-the-art open-weight coding (topped swe-bench pro at launch). Choose GLM 5.1 if you need self-hosting or data privacy; Claude Fable 5.1 if you want a managed API.
Claude Fable 5.1 (Anthropic, US) and GLM 5.1 (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 5.1 is anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. GLM 5.1 is an open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. 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 5.1 is about 7.1× cheaper on input ($1.4/$4.4 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 5.1 holds 5× more — 1M tokens (~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: Claude Fable 5.1 is the newer model by about 5 months (released September 1, 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 5.1
GLM 5.1
Provider
Anthropic (US)
Z.ai (China)
Released
September 1, 2026
April 7, 2026
Context window
1M tokens (~1,500 pages)
200K (~300 pages)
Price (in/out)
$10/$50 per 1M tokens
$1.4/$4.4 per 1M tokens
Open weight?
No — API only
Yes — self-hostable
Modalities
text, image
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%)
Claude Fable 5.1
Anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores — and it carries the larger 1M tokens context.
CursorBench 3.2 agentic coding (73.4%)
Claude Fable 5.1
Anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores — and it is the newer of the two.
Cache-read pricing cut to a quarter of other Claude models
Claude Fable 5.1
Claude Fable 5.1 lists cache-read pricing cut to a quarter of other Claude models among its strengths; GLM 5.1 does not.
Long-horizon autonomous agentic engineering (up to 8-hour runs)
GLM 5.1
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours — and it runs cheaper at $1.4/$4.4 per 1M tokens.
State-of-the-art open-weight coding (topped SWE-Bench Pro at launch)
GLM 5.1
Open weights make this possible at all — Claude Fable 5.1 is API-only, so it cannot leave the vendor's servers.
Sustained tool use across thousands of calls
GLM 5.1
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours — and its weights are open while Claude Fable 5.1 is API-only.
Lowest cost at scale
GLM 5.1
At $1.4/$4.4 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 5.1
Its 1M tokens window is about 5× larger than GLM 5.1's 200K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GLM 5.1
At $1.4/$4.4 per 1M tokens it undercuts Claude Fable 5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Claude Fable 5.1
Larger 1M tokens window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ GLM 5.1
Open weights let you run it on your own hardware; Claude Fable 5.1 is API-only.
Anyone whose priority is terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%)
→ Claude Fable 5.1
It is specifically built for that.
Anyone whose priority is long-horizon autonomous agentic engineering (up to 8-hour runs)
→ GLM 5.1
That is its strongest area.
An enterprise with regional data-residency rules
→ Claude Fable 5.1 or GLM 5.1
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Fable 5.1: where it fits
Anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. Released September 1, 2026 by Anthropic, it is built for terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%), cursorBench 3.2 agentic coding (73.4%), cache-read pricing cut to a quarter of other Claude models, and long, multistep, document-heavy professional work with 1M-token context.
Its trade-offs are real: anthropic has not published an official SWE-bench Verified score for this model, restricted Mythos 5.1 variant outscores it on some benchmarks due to lighter safeguards (Terminal-Bench 4.0: 60.9% vs 55.8%), and closed weights, no self-hosting option. At $10 in / $50 out per million tokens, it sits in the premium price band.
GLM 5.1: where it fits
An open-weight (MIT) Chinese coding model built for long-horizon agentic engineering, topping SWE-Bench Pro at launch while running autonomously for up to 8 hours. Released April 7, 2026 by Z.ai, it is built for long-horizon autonomous agentic engineering (up to 8-hour runs), state-of-the-art open-weight coding (topped SWE-Bench Pro at launch), sustained tool use across thousands of calls, and self-hostable under a permissive MIT license.
Its trade-offs: text-only, with no image, audio, or video input, and 754B-parameter MoE demands heavy GPU resources to self-host. At $1.4 in / $4.4 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 5.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Claude Fable 5.1 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 5.1 and GLM 5.1 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, Claude Fable 5.1 leans toward terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) while GLM 5.1 leans toward long-horizon autonomous agentic engineering (up to 8-hour runs), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Fable 5.1 or GLM 5.1?
GLM 5.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Fable 5.1 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 5.1 — 1M tokens vs 200K, about 5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Claude Fable 5.1 and GLM 5.1 together?
Yes — a multi-model platform like LumiChats gives you Claude Fable 5.1, GLM 5.1 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 5.1 or GLM 5.1?
Claude Fable 5.1 — released September 1, 2026, about 5 months after GLM 5.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.