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Claude Fable 5.1 vs GLM-5.3

Claude Fable 5.1 is served by invitation. Its figures below are the live rates, but calls need a workspace grant first; ask us for access before you build on this comparison.

vs

Which one, when

Both claude-fable-5-1 and glm-5.3 give you a 1,000,000-token context with tool use and reasoning, and near-identical cache reads ($0.25 versus $0.26), so the real split is image input and price: claude-fable-5-1 accepts text and image, while glm-5.3 is text-only and costs about 7.1x less on input ($1.4 versus $10) and about 11.4x less on output ($4.4 versus $50). Pick claude-fable-5-1 when a task needs images alongside its explicit thinking capability; pick glm-5.3 for high-volume text and long-context work, where its slightly larger 131,072-token max output also helps.

Benchmarks

Above averageNo peer higherClaude Fable 5.17 / 77 / 7GLM-5.314 / 161 / 16
Claude Fable 5.1 GLM-5.3 other models measured peer average no peer scored higher
Terminal-Bench 2.1
N/A
88.2%
OSWorld 2.0 partial
77.9%
N/A
Cybergym
N/A
no peer scored higher 84.5%
GDPval-AA v2 Elo · 1711-1853 per Anthropic · 2026-09-05
no peer scored higher 1853
N/A
Humanity's Last Exam with tools
no peer scored higher 65%
62.5%
Agents' Last Exam
N/A
28.5%

Vendor-published: Alibaba (Qwen) Anthropic DeepSeek Google MiniMax Moonshot OpenAI Tencent Z.ai

Pricing

Claude Fable 5.1 GLM-5.3 Δ
Input / 1M tokens $10 $1.4 7.1×
Output / 1M tokens $50 $4.4 11×
Cache read / 1M tokens $0.25 $0.26 0.96×
Cache write 1.25x (5m) / 2x (1h) - -

Rates from the live catalog at build time; each model page carries the current card.

Where they sit - input price per 1M tokens across all 67 chat models on this billing unit (log scale)

Claude Fable 5.1 · $10 GLM-5.3 · $1.4
$0.05 · Qwen3 VL Flash $30 · GPT-5.4 Pro

Capabilities

Claude Fable 5.1 GLM-5.3
Tool use yes yes
Thinking control always on always on
Structured output yes yes
Prompt caching explicit (you mark the prefix) implicit (automatic)
Cache lifetime 5m default, 1h option not published
Minimum cached prefix 1024 tokens not published

Specs

Claude Fable 5.1 GLM-5.3
Input modalities text image text
Output modalities text text
Released 2026-09-01 -
Knowledge cutoff 2026-06 -
Context window 1M 1M
Max output 128K 131K
Thinking parameter output_config.effort (thinking is adaptive-only and always on) reasoning_effort
Accepted values
effort
  • low
  • medium
  • high
  • xhigh
  • max
reasoning_effort
  • low
  • high
  • max
Default

thinking always on (adaptive)

effort
  • high
max

Specs are transcribed from each vendor’s documentation; a row a vendor does not publish is left out rather than inferred. Full sources: Claude Fable 5.1 · GLM-5.3

Switch between them with one line

Both ids are in every tab below - the highlighted pair of lines is the only edit. Same endpoint, same key, same request shape.

from openai import OpenAI

client = OpenAI(
    base_url="https://synthorai.io/v1",
    api_key="sk-syn-...",
)

resp = client.chat.completions.create(
    model="claude-fable-5-1",
    # model="glm-5.3",  # uncomment this line, comment the one above
    messages=[{"role": "user", "content": "Summarize this diff"}],
    reasoning_effort="medium",
)
print(resp.choices[0].message.content)

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FAQ

Which is cheaper, Claude Fable 5.1 or GLM-5.3?

GLM-5.3 is cheaper on input / 1m tokens ($1.4 vs $10, 7.1× apart). Other rows may point the other way - the table above carries the full card, and real cost depends on your mix.

Can I A/B test Claude Fable 5.1 against GLM-5.3 without two integrations?

Yes. Both are served through the same OpenAI-compatible endpoint with one API key - switching is a one-line model-string change, so you can route a fraction of traffic to each and compare bills directly.

Do Claude Fable 5.1 and GLM-5.3 support prompt caching?

Yes - both bill cached reads below their input rate, so warm-prefix workloads cost less than the list rates suggest. The exact cache-read rows are in the pricing table above.

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