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BenchLM
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Model A
Claude Fable 5

Anthropic

81.43/100

Supported · Public rank #5

90% interval 77.6–85.3

Claude Fable 5 vs GPT Realtime 2.1

Updated September 10, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

OpenAI logo
Model B
GPT Realtime 2.1

OpenAI

—

Evidence status unavailable

90% interval unavailable

Decision reading

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 results are shared. Category rows resting on Estimated evidence or different benchmark sets are marked directional and do not name a winner.

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Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

  • Long documents

    Prompts that approach the documented context limit

    Claude Fable 5

    Claude Fable 5 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    GPT Realtime 2.1

    GPT Realtime 2.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

Show secondary and unsupported calls

  • Repository review cost

    50K fresh input + 3K output tokens

    GPT Realtime 2.1

    GPT Realtime 2.1 has the lower estimated token cost for this stated workload. Costs use the listed standard API rates.

    Confidence: listed-rates

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    GPT Realtime 2.1 is not ranked on the public lane for coding, so no winner is named for coding.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    GPT Realtime 2.1 is not ranked on the public lane for agentic, so no winner is named for agentic.

    Confidence: limited

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. GPT Realtime 2.1 does not fit this workload in one request.

    Confidence: listed-rates

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Shared results
0
Claude Fable 5 only
18
GPT Realtime 2.1 only
0
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row shows the public-lane category score for both models: the BenchAlign lane for agentic, coding, and knowledge, and the weighted public rows elsewhere, with the same rank each model page reports. A row is like-for-like only when both scores rest on Supported evidence or the same weighted set. Directional and not-comparable rows remain visible, but they never receive a winner.

Agentic

Not comparable
Claude Fable 5
74.6
Supported · #3/152
GPT Realtime 2.1
Not ranked
Basis
BenchAlign lane · 4 vs 0 public rows
Reading
Not comparable

Coding

Not comparable
Claude Fable 5
77.0
Supported · #2/151
GPT Realtime 2.1
Not ranked
Basis
BenchAlign lane · 10 vs 0 public rows
Reading
Not comparable

Reasoning

Not comparable
Claude Fable 5
77.6
#6/20
GPT Realtime 2.1
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Knowledge

Not comparable
Claude Fable 5
83.3
Supported · #2/183
GPT Realtime 2.1
Not ranked
Basis
BenchAlign lane · 2 vs 0 public rows
Reading
Not comparable

Math

Not comparable
Claude Fable 5
Not ranked
GPT Realtime 2.1
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multilingual

Not comparable
Claude Fable 5
Not ranked
GPT Realtime 2.1
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Multimodal

Not comparable
Claude Fable 5
62.5
Unranked · 2 rankable rows
GPT Realtime 2.1
Not ranked
Basis
Provisional lane · 1 vs 0 weighted rows
Reading
Not comparable

Instruction following

Not comparable
Claude Fable 5
78.5
#56/123
GPT Realtime 2.1
Not ranked
Basis
Provisional lane · 0 vs 0 weighted rows
Reading
Not comparable

Ranks count the models scored in each category’s lane, so the agentic, coding, and knowledge denominators (BenchAlign) differ from the provisional-lane categories. Unranked scores sit on the lane’s scale but never name a winner. Like-for-like rows within 0.5 points read as a practical tie.

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

Claude Fable 5
$0.035
Fits in one request
GPT Realtime 2.1
$0.016
Fits in one request

GPT Realtime 2.1 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Fable 5
$0.65
Fits in one request
GPT Realtime 2.1
$0.272
Fits in one request

GPT Realtime 2.1 has the lower modeled cost

Costs use the listed standard API rates.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

Claude Fable 5
$0.9
Fits in one request
GPT Realtime 2.1
$0.4
Does not fit in one request

GPT Realtime 2.1 does not fit this workload in one request.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

Claude Fable 5

$1 per 1M cached input tokens

Claude API pricing

GPT Realtime 2.1

$0.4 per 1M cached input tokens

OpenAI model documentation

Reasoning profile

Claude Fable 5

Reasoning

GPT Realtime 2.1

Non-Reasoning

Weight access

Claude Fable 5

Proprietary

GPT Realtime 2.1

Proprietary

License

Claude Fable 5

Proprietary

GPT Realtime 2.1

Proprietary

Release date

Claude Fable 5

2026-06-09

GPT Realtime 2.1

2026-07-06

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
Repository review: $0.65 vs $0.272. Cache-heavy agent loop: $0.9 vs $0.4.
Context tradeoff
Claude Fable 5 has the larger documented window (1M).

Run the same representative tasks against both endpoints before changing production traffic.

Benchmark evidence

The full public result ledger is available for audit without forcing a wide desktop table onto a phone.

Browse raw public benchmark evidence18 rows

Agentic

  • Terminal-Bench 3.0

    Claude Fable 534.0%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • OSWorld-Verified

    Claude Fable 585%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • Terminal-Bench 2.1 (Vals)

    Claude Fable 580.5%
    Source
    GPT Realtime 2.1—

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Fable 595%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • SWE-bench Pro

    Claude Fable 580%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • FrontierSWE v2

    Claude Fable 547.0%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Fable 553.5%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Fable 584.3%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • cursorBench31

    Claude Fable 570.6%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • cursorBench32

    Claude Fable 570.5%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • VulcanBench v3

    Claude Fable 589.5%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • LiveCodeBench (Vals)

    Claude Fable 589.8%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • SWE-bench (Vals)

    Claude Fable 595.0%
    Source
    GPT Realtime 2.1—

    Not directly comparable

Knowledge

  • GPQA Diamond (Vals)

    Claude Fable 593.2%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • MMLU-Pro (Vals)

    Claude Fable 591.5%
    Source
    GPT Realtime 2.1—

    Not directly comparable

Multimodal

  • Blueprint-Bench 2

    Claude Fable 538.6%
    Source
    GPT Realtime 2.1—

    Not directly comparable

  • OfficeQA Pro

    Claude Fable 557.9%
    Source
    GPT Realtime 2.1—

    Not directly comparable

Frequently asked questions

Which is better, Claude Fable 5 or GPT Realtime 2.1?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, Claude Fable 5 or GPT Realtime 2.1?

GPT Realtime 2.1 is not ranked on the public lane for coding, so no winner is named for coding.

Which is better for agentic tasks, Claude Fable 5 or GPT Realtime 2.1?

GPT Realtime 2.1 is not ranked on the public lane for agentic tasks, so no winner is named for agentic tasks.

Which costs less, Claude Fable 5 or GPT Realtime 2.1?

For the stated presets, chat costs $0.035 on Claude Fable 5 and $0.016 on GPT Realtime 2.1; repository review costs $0.65 and $0.272; the cache-heavy agent loop costs $0.9 and $0.4. GPT Realtime 2.1 does not fit this workload in one request.

Which has the larger context window, Claude Fable 5 or GPT Realtime 2.1?

Claude Fable 5 has the larger documented context window: 1M, compared with 128K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated September 10, 2026

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