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Dola Seed 2.0 Pro vs Claude Fable 5.1

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

Dola-Seed-2.0-pro is the cheaper unit of work by a wide margin - $0.5 versus $10 per million input tokens (20x) and $3 versus $50 on output (about 16.7x) - and it is the only one of the two that accepts video input and lets you turn thinking off, so pick it for high-volume chat, code and tool work where you want control over reasoning cost. Choose claude-fable-5-1 when the job needs its 1,000,000-token context rather than 256,000, and accept that thinking cannot be disabled and inputs are text and image only. Both cache reads are cheap, at $0.1 and $0.25 per million.

Benchmarks

Dola Seed 2.0 Pro: the vendor has not published benchmark scores.

Above averageNo peer higherClaude Fable 5.17 / 77 / 7
Dola Seed 2.0 Pro Claude Fable 5.1 other models measured peer average no peer scored higher
Terminal-bench 4.0
N/A
no peer scored higher 55.8%
OSWorld 2.0 partial
N/A
77.9%
GDPval-AA v2 Elo · 1711-1853 per Anthropic · 2026-09-05
N/A
no peer scored higher 1853
Humanity's Last Exam no tools
N/A
no peer scored higher 60.9%
AutomationBench
N/A
no peer scored higher 31.4%

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

Pricing

Dola Seed 2.0 Pro Claude Fable 5.1 Δ
Input / 1M tokens $0.5 $10 0.05×
Output / 1M tokens $3 $50 0.06×
Cache read / 1M tokens $0.1 $0.25 0.4×
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)

Capabilities

Dola Seed 2.0 Pro Claude Fable 5.1
Tool use yes yes
Thinking control configurable always on
Structured output - yes
Prompt caching implicit + explicit explicit (you mark the prefix)
Cache lifetime not published 5m default, 1h option
Minimum cached prefix 1024 tokens 1024 tokens

Specs

Dola Seed 2.0 Pro Claude Fable 5.1
Input modalities text image video text image
Output modalities text text
Released 2026-02-14 2026-09-01
Knowledge cutoff - 2026-06
Context window 256K 1M
Max output 131K 128K
Thinking parameter
  • thinking.type
  • reasoning_effort
output_config.effort (thinking is adaptive-only and always on)
Accepted values
thinking.type
  • enabled
  • disabled (no auto)
reasoning_effort
  • minimal
  • low
  • medium
  • high
effort
  • low
  • medium
  • high
  • xhigh
  • max
Default enabled, with reasoning_effort medium and thinking summary on

thinking always on (adaptive)

effort
  • high

Specs are transcribed from each vendor’s documentation; a row a vendor does not publish is left out rather than inferred. Full sources: Dola Seed 2.0 Pro · Claude Fable 5.1

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="Dola-Seed-2.0-pro",
    # model="claude-fable-5-1",  # 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, Dola Seed 2.0 Pro or Claude Fable 5.1?

Dola Seed 2.0 Pro is cheaper on input / 1m tokens ($0.5 vs $10, 20× 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 Dola Seed 2.0 Pro against Claude Fable 5.1 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 Dola Seed 2.0 Pro and Claude Fable 5.1 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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