Model comparison · accepted catalogue facts 2026-10-21

Claude Sonnet 5.5 vs GPT-5.6 Sol

Claude Sonnet 5.5 has an equal-or-higher measured score and an equal-or-lower estimated price. Switching from GPT-5.6 Sol loses capability or fails a requirement. Review the migration checks. The reported score intervals do not overlap; this is not a task-specific success guarantee.

Editorial comparison: Anthropic Sonnet 5.5 vs OpenAI Sol in coding and general workloads Inclusion does not recommend either model.

Claude Sonnet 5.5

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1470.6

Balanced effective USD / 1M tokens · lower is better

$4.00/M

GPT-5.6 Sol

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1457.2

Balanced effective USD / 1M tokens · lower is better

$8.00/M

In-Depth Analysis

Claude Sonnet 5.5 vs GPT-5.6 Sol: Measured Technical Breakdown

Comprehensive comparison across measured human-preference evaluation, effective production token costs, architectural limits, and migration trade-offs.

Measured Capability (LMArena)

Claude Sonnet 5.5 leads by 13.4 Elo

Claude Sonnet 5.5: 1470.6 ±7.96 · GPT-5.6 Sol: 1457.2 ±4.34 Statistically significant preference separation

Cost Comparison Across Canonical Production Workloads

Rates represent effective cost per 1M tokens under standard token blends. Cached prompt reads are factored according to workload context reuse.

Workload & Ratio	Claude Sonnet 5.5	GPT-5.6 Sol	Cost Difference	Advantage
Balanced 3 tokens in per 1 out	$4.00 /1M tokens	$8.00 /1M tokens	$4.00 (50% diff)	Claude Sonnet 5.5 costs less
Summarise Huge input, tiny output	$1.86 /1M tokens	$3.77 /1M tokens	$1.92 (51% diff)	Claude Sonnet 5.5 costs less
Chat Long cached system prompt	$4.63 /1M tokens	$9.32 /1M tokens	$4.69 (50% diff)	Claude Sonnet 5.5 costs less
Code gen Output dominates	$6.65 /1M tokens	$13.31 /1M tokens	$6.66 (50% diff)	Claude Sonnet 5.5 costs less
Agentic Context replayed each turn	$2.07 /1M tokens	$4.26 /1M tokens	$2.19 (51% diff)	Claude Sonnet 5.5 costs less

Architectural & Operational Specifications

Specification	Claude Sonnet 5.5	GPT-5.6 Sol	Operational Note
Context window	1,000,000 tokens	1,050,000 tokens	GPT-5.6 Sol has a 1.1× larger context window
Max output generation	128,000 tokens	128,000 tokens	—
Base input price	$2.00 / 1M tokens	$4.00 / 1M tokens	Claude Sonnet 5.5 input rate is cheaper
Base output price	$10.00 / 1M tokens	$20.00 / 1M tokens	Claude Sonnet 5.5 output rate is cheaper
Cached input price	$0.100 / 1M tokens	$0.400 / 1M tokens	Claude Sonnet 5.5 offers lower cached prompt cost
Reasoning & thinking tokens	Supported; standard rates	Supported; standard rates	—
Input modalities	text, image, file	file, image, text	—
Tool calling / function use	Supported	Supported	—
Open weights & licence	Proprietary (API-only)	Proprietary (proprietary)	—
Provider & reseller market	Anthropic · 8 provider offers	OpenAI · 7 provider offers (2.2× spread)	—

When to Choose Claude Sonnet 5.5

Higher measured general capability (1470.6 Elo on human evaluation).
Direct integration with Anthropic tooling and API features.

Risks when moving from GPT-5.6 Sol → Claude Sonnet 5.5:

Context window: 1,050,000 → 1,000,000 tokens.

When to Choose GPT-5.6 Sol

Larger context window (1,050,000 tokens) for long-document or repo-level context.
Direct integration with OpenAI tooling and API features.

Detailed Evidence Passports & Independent Audits

Claude Sonnet 5.5 Full model card, pricing ladder & provider offers → GPT-5.6 Sol Full model card, pricing ladder & provider offers → Alternatives to Claude Sonnet 5.5 Better-and-cheaper dominance audit → Alternatives to GPT-5.6 Sol Better-and-cheaper dominance audit →

Compare · model decision

Choose two or three models

Inspect the differences, estimate your workload and keep the evidence. All standard catalogue models are available, including unrated ones.

Catalogue facts
2026-10-21

A · Current or starting modelB · Comparison modelC · Optional third model

2 / 3 selected · 0 requirements

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Public workload and requirements

These settings are included in the share link. The fixed-request scenario and private evaluation data below are excluded.

Workload Public prompt length (tokens) Required context (tokens) Required output limit (tokens) Required input modality

Tool useReasoningOpen weights

A ↔ B

Estimated blend: 75% input, 25% output; 0% cached input. Base context tier. Prompt length selects the billing tier. An unlisted cache-read rate uses that tier’s full input rate in this blend; missing required input or output rates prevent an estimate. The fixed-request estimate below validates actual context and output limits and requires a published cache-read rate when cache hits are assumed.

What changes between these models

Quality first, then estimated price. LMArena scores are human-preference measurements, not a benchmark of your application. A missing score is unrated.

Claude Sonnet 5.5 · Meets the stated model requirements
GPT-5.6 Sol · Meets the stated model requirements

Material differences and unknown evidence. Deltas compare each model with model A. Unknown facts remain visible.
Measured fact	A Claude Sonnet 5.5	B GPT-5.6 Sol
LMArena general score (Elo)	1,470.6	1,457.2Δ vs A: -13.4 Elo
Score interval half-width (± Elo)	7.96	4.34Δ vs A: -3.62 Elo
LMArena document score (Elo)	Unknown	1,482.7
Estimated effective USD / 1M tokens	$4	$8Δ vs A: +4 USD/M
Base input USD / 1M tokens	$2	$4Δ vs A: +2 USD/M
Base output USD / 1M tokens	$10	$20Δ vs A: +10 USD/M
Base cached-input USD / 1M tokens	$0.1	$0.4Δ vs A: +0.3 USD/M
Context window (tokens)	1,000,000	1,050,000Δ vs A: +50,000 tokens
Input modalities	text, image, file	file, image, text
Recorded licence	Unknown	proprietary
Model provider	Anthropic	OpenAI
Distinct sellers in the catalogue	5	3Δ vs A: -2
Recorded retirement date	Unknown	Unknown

7 shared measured facts

Shared measured facts. Deltas compare each model with model A. Unknown facts remain visible.
Measured fact	A Claude Sonnet 5.5	B GPT-5.6 Sol
Benchmark reasoning effort	xhigh	xhigh
Output limit (tokens)	128,000	128,000Δ vs A: 0 tokens
Tool use	Supported	SupportedΔ vs A: 0
Reasoning	Supported	SupportedΔ vs A: 0
Open weights	Not supported	Not supportedΔ vs A: 0
Serving precision differs across offers	Not supported	Not supportedΔ vs A: 0
Retirement evidence	None announced; not a guarantee	None announced; not a guarantee

Provider counts and precision flags describe catalogue offers. They do not establish the precision, availability, region, tool behaviour or limits of your chosen endpoint. Open each model’s provider table before switching.

Complete price ladders and billing conditions

Claude Sonnet 5.5

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token threshold	Input	Output	Cached input
Base, up to and including first threshold	$2	$10	$0.1

GPT-5.6 Sol

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token threshold	Input	Output	Cached input
Base, up to and including first threshold	$4	$20	$0.4
> 272,000	$8	$30	$0.8

Migration preflight · compare each candidate with model A

Keeping Claude Sonnet 5.5 is a valid decision. No pairwise comparison certifies a drop-in replacement.

Claude Sonnet 5.5 → GPT-5.6 Sol

No known model-capability loss

Provider endpoint, serving precision, availability and task success need your own verification. Catalogue model capabilities do not certify an endpoint.

Check alternatives to Claude Sonnet 5.5

Estimate a fixed request shape

Private to this tab unless you save locally or explicitly export private details. These are estimates, not observed invoices. Cross-model token counts and task success are assumptions.

Requests Input tokens per request Output tokens per request Cached share of input (%) Extra attempts per request

0.1 extra attempts means 10 extra full attempts per 100 requests. Cache writes, tool charges, taxes and unlisted charges are excluded.

Claude Sonnet 5.5Estimated total: $9 1,000 full attempts · base rates
GPT-5.6 SolEstimated total: $18 1,000 full attempts · base rates

Prompt and output sensitivity · sampled scenarios

Every point recalculates the entire request shape. Tier-boundary samples include one token below, at and above each threshold. Ordering between samples is not guaranteed. Lowest known cost excludes unknown estimates and is not a replacement recommendation.

Vary input; hold output, requests, cache and retries fixed.
Input tokens	Claude Sonnet 5.5	GPT-5.6 Sol	Coverage
2,000	$9Lowest known	$18	All computed
4,096	$13.192Lowest known	$26.384	All computed
32,768	$70.536Lowest known	$141.072	All computed
131,072	$267.144Lowest known	$534.288	All computed
271,999	$548.998Lowest known	$1,097.996	All computed
272,000	$549Lowest known	$1,098	All computed
272,001	$549.002Lowest known	$2,191.008	All computed

Vary output; hold input, requests, cache and retries fixed.
Output tokens	Claude Sonnet 5.5	GPT-5.6 Sol
128	$5.28	$10.56
2,048	$24.48	$48.96
8,192	$85.92	$171.84

Bring your observed evaluation results

JSON is parsed locally. Prompts, filenames, individual responses and extra fields are not retained. Import only aggregate measurements for selected models. Task/version labels do not establish that two evaluations used the same dataset.

Import private evaluation JSON

Expected format

[{"model":"provider/exact-model-id","task":"support-answer","version":"rubric-1","attempts":100,"successes":84,"costUsd":2.4,"latencyMs":950}]

Use the exact catalogue ID. Replace the example values with observed measurements. Omit costUsd or latencyMs when they are unknown. No public score is inferred from these observations.

Keep the decision and its evidence

A portable record retains selected facts, complete tier ladders, public requirements and the publication manifest. It also embeds the full permitted public catalogue to verify the input artifact checksum. Files are larger for this reason (up to 2 MB); local storage is limited to 12 records. Team review is local to this browser; there is no hosted collaboration.

Owner (private) Review date (private) Recorded choice (private) Rationale (private)

Include private review fields, scenario and observations in downloaded files

Store private decision records on this device

Saving is opt-in and includes private review fields. Shared comparison links never include them. Version 1 Check references remain separate and are not overwritten or guessed into this format.

Import a v2 decision JSON file

Saved local decisions · 0

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Questions this page answers

Is Claude Sonnet 5.5 a better-and-cheaper replacement for GPT-5.6 Sol?

Which model is higher rated: Claude Sonnet 5.5 or GPT-5.6 Sol?

Claude Sonnet 5.5 scores higher on LMArena general (1470.6 ±8.0) compared to GPT-5.6 Sol (1457.2 ±4.3), a margin of 13.4 Elo points. The measured confidence intervals do not overlap, demonstrating a statistically significant preference lead on human evaluations.

Which model is more cost-effective: Claude Sonnet 5.5 or GPT-5.6 Sol?

On a standard balanced workload (3 prompt tokens per 1 generated token), Claude Sonnet 5.5 costs $4.00 per 1M tokens versus $8.00 for GPT-5.6 Sol. GPT-5.6 Sol is approximately 2.0× the price of Claude Sonnet 5.5. Base input rates are $2.00 for Claude Sonnet 5.5 and $4.00 for GPT-5.6 Sol; base output rates are $10.00 for Claude Sonnet 5.5 and $20.00 for GPT-5.6 Sol.

How do their context windows and generation limits compare?

Claude Sonnet 5.5 provides a 1,000,000-token context window with a maximum output limit of 128,000 tokens. GPT-5.6 Sol provides a 1,050,000-token context window with a maximum output of 128,000 tokens.

What capabilities are lost when switching between Claude Sonnet 5.5 and GPT-5.6 Sol?

Switching from Claude Sonnet 5.5 to GPT-5.6 Sol causes no detected architectural capability loss. Conversely, moving from GPT-5.6 Sol to Claude Sonnet 5.5 involves: Context window: 1,050,000 → 1,000,000 tokens. Run test suites on your specific prompt templates and tool declarations before cutting over production traffic.

Can Claude Sonnet 5.5 or GPT-5.6 Sol be self-hosted or deployed privately?

Both Claude Sonnet 5.5 and GPT-5.6 Sol are proprietary cloud models offered via managed API endpoints. Claude Sonnet 5.5 is served by Anthropic and 8 catalogue offers, while GPT-5.6 Sol is served by OpenAI and 7 catalogue offers.

What is included in this comparison?

Accepted model capabilities, context and output limits, complete price-tier ladders, independent LMArena measurements and missing evidence. Provider endpoint precision and application success still need verification.

Can I compare a different workload or keep a decision record?

Yes. Change the public workload, prompt length and requirements in the comparison workspace. Fixed-request scenarios, aggregate evaluations and review notes stay local unless explicitly exported.

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Claude Sonnet 5.5 vs GPT-5.6 Sol

Claude Sonnet 5.5 vs GPT-5.6 Sol: Measured Technical Breakdown

Cost Comparison Across Canonical Production Workloads

Architectural & Operational Specifications

When to Choose Claude Sonnet 5.5

When to Choose GPT-5.6 Sol

Detailed Evidence Passports & Independent Audits

Choose two or three models

What changes between these models

Claude Sonnet 5.5

GPT-5.6 Sol

Claude Sonnet 5.5 → GPT-5.6 Sol

Estimate a fixed request shape

Bring your observed evaluation results

Keep the decision and its evidence

Saved local decisions · 0

Questions this page answers