Skip to main content

Model comparison

Claude Sonnet 5 vs GPT Realtime 1.5

Updated August 4, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

Claude Sonnet 5

Anthropic

64.5/100

Estimated · Public rank #35

90% interval 50.0–79.0

GPT Realtime 1.5

OpenAI

Evidence status unavailable

90% interval unavailable

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 based on different benchmark sets are marked directional and do not name a winner.

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 Sonnet 5

    Claude Sonnet 5 has the larger documented context window.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Claude Sonnet 5

    Claude Sonnet 5 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
  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

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

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    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 1.5 does not fit this workload in one request.

    Confidence: listed-rates

  • Repository review cost

    50K fresh input + 3K 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 1.5 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 Sonnet 5 only
15
GPT Realtime 1.5 only
0
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable
Claude Sonnet 5
81.9
GPT Realtime 1.5
Not measured
Weighted basis
3 vs 0 rows
Reading
Not comparable

Coding

Not comparable
Claude Sonnet 5
76.7
GPT Realtime 1.5
Not measured
Weighted basis
2 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
Claude Sonnet 5
Not measured
GPT Realtime 1.5
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
Claude Sonnet 5
57.4
GPT Realtime 1.5
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Math

Not comparable
Claude Sonnet 5
Not measured
GPT Realtime 1.5
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
Claude Sonnet 5
Not measured
GPT Realtime 1.5
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
Claude Sonnet 5
88.3
GPT Realtime 1.5
Not measured
Weighted basis
1 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
Claude Sonnet 5
Not measured
GPT Realtime 1.5
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

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 Sonnet 5
$0.007
Fits in one request
GPT Realtime 1.5
$0.012
Fits in one request

Claude Sonnet 5 has the lower modeled cost

Costs use the listed standard API rates.

Repository review

50K fresh input + 3K output tokens

Claude Sonnet 5
$0.13
Fits in one request
GPT Realtime 1.5
$0.248
Does not fit in one request

GPT Realtime 1.5 does not fit this workload in one request.

Cache-heavy agent loop

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

Claude Sonnet 5
$0.18
Fits in one request
GPT Realtime 1.5
$0.32
Does not fit in one request

GPT Realtime 1.5 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 Sonnet 5

$0.2 per 1M cached input tokens

Claude API pricing

GPT Realtime 1.5

$0.4 per 1M cached input tokens

OpenAI model documentation

Provider availability

Claude Sonnet 5

Generally Available · Claude API

Anthropic model overview

GPT Realtime 1.5

Not sourced

Reasoning profile

Claude Sonnet 5

Reasoning

GPT Realtime 1.5

Non-Reasoning

Weight access

Claude Sonnet 5

Proprietary

GPT Realtime 1.5

Proprietary

License

Claude Sonnet 5

Proprietary

GPT Realtime 1.5

Proprietary

Release date

Claude Sonnet 5

2026-06-30

GPT Realtime 1.5

2026-02-01

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: $0.13 vs $0.248. Cache-heavy agent loop: $0.18 vs $0.32.
Context tradeoff
Claude Sonnet 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 evidence15 rows

Agentic

  • Terminal-Bench 2.0

    Claude Sonnet 580.4%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • BrowseComp

    Claude Sonnet 584.7%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • HLE w/ tools

    Claude Sonnet 557.4%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • OSWorld-Verified

    Claude Sonnet 581.2%
    Source
    GPT Realtime 1.5

    Not directly comparable

Coding

  • SWE-bench Verified

    Claude Sonnet 585.2%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • SWE-bench Pro

    Claude Sonnet 563.2%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • SWE Multilingual

    Claude Sonnet 578.3%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • SWE Multimodal

    Claude Sonnet 528.1%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • Terminal-Bench 2.0

    Claude Sonnet 580.4%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • FrontierCode 1.1 Main

    Claude Sonnet 542.7%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • cursorBench32

    Claude Sonnet 561.5%
    Source
    GPT Realtime 1.5

    Not directly comparable

Knowledge

  • HLE

    Claude Sonnet 557.4%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • HLE w/o tools

    Claude Sonnet 543.2%
    Source
    GPT Realtime 1.5

    Not directly comparable

Multimodal

  • CharXiv

    Claude Sonnet 588.3%
    Source
    GPT Realtime 1.5

    Not directly comparable

  • CharXiv w/o tools

    Claude Sonnet 577%
    Source
    GPT Realtime 1.5

    Not directly comparable

Frequently asked questions

Which is better, Claude Sonnet 5 or GPT Realtime 1.5?

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 Sonnet 5 or GPT Realtime 1.5?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, Claude Sonnet 5 or GPT Realtime 1.5?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, Claude Sonnet 5 or GPT Realtime 1.5?

For the stated presets, chat costs $0.007 on Claude Sonnet 5 and $0.012 on GPT Realtime 1.5; repository review costs $0.13 and $0.248; the cache-heavy agent loop costs $0.18 and $0.32. GPT Realtime 1.5 does not fit this workload in one request.

Which has the larger context window, Claude Sonnet 5 or GPT Realtime 1.5?

Claude Sonnet 5 has the larger documented context window: 1M, compared with 32K.

Related comparisons

Last updated August 4, 2026

Watch Claude Sonnet 5 vs GPT Realtime 1.5

One weekly email when material rank, price, or benchmark evidence changes make this matchup worth revisiting.

Read a sample issue

Join 2,000+ readers.