Model comparison · accepted catalogue facts 2026-10-21
Claude Sonnet 4.6 vs GPT-5.6 Sol
Claude Sonnet 4.6 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 overlap; this is not an established quality improvement.
Editorial comparison: Direct benchmark rivals: Claude Sonnet 4.6 (Anthropic) vs GPT-5.6 Sol (OpenAI) with overlapping confidence intervals Inclusion does not recommend either model.
Balanced effective USD / 1M tokens · lower is better
$8.00/M
In-Depth Analysis
Claude Sonnet 4.6 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 4.6 leads by 0.6 Elo
Claude Sonnet 4.6: 1457.8 ±3.5 · GPT-5.6 Sol: 1457.2 ±4.34 Intervals overlap — not a guaranteed quality advantage
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 4.6
GPT-5.6 Sol
Cost Difference
Advantage
Balanced3 tokens in per 1 out
$6.00/1M tokens
$8.00/1M tokens
$2.00(25% diff)
Claude Sonnet 4.6 costs less
SummariseHuge input, tiny output
$2.83/1M tokens
$3.77/1M tokens
$0.944(25% diff)
Claude Sonnet 4.6 costs less
ChatLong cached system prompt
$6.99/1M tokens
$9.32/1M tokens
$2.33(25% diff)
Claude Sonnet 4.6 costs less
Code genOutput dominates
$9.98/1M tokens
$13.31/1M tokens
$3.33(25% diff)
Claude Sonnet 4.6 costs less
AgenticContext replayed each turn
$3.19/1M tokens
$4.26/1M tokens
$1.06(25% diff)
Claude Sonnet 4.6 costs less
Architectural & Operational Specifications
Specification
Claude Sonnet 4.6
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
$3.00 / 1M tokens
$4.00 / 1M tokens
Claude Sonnet 4.6 input rate is cheaper
Base output price
$15.00 / 1M tokens
$20.00 / 1M tokens
Claude Sonnet 4.6 output rate is cheaper
Cached input price
$0.300 / 1M tokens
$0.400 / 1M tokens
Claude Sonnet 4.6 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 (proprietary)
Proprietary (proprietary)
—
Provider & reseller market
Anthropic · 9 provider offers
OpenAI · 7 provider offers (2.2× spread)
—
When to Choose Claude Sonnet 4.6
Higher measured general capability (1457.8 Elo on human evaluation).
Direct integration with Anthropic tooling and API features.
Risks when moving from GPT-5.6 Sol → Claude Sonnet 4.6:
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.
These settings are included in the share link. The fixed-request scenario and private evaluation data below are excluded.
A ↔ B
Claude Sonnet 4.6 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 overlap; this is not an established quality improvement.
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 4.6 · 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.
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.
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 4.6 is a valid decision. No pairwise comparison certifies a drop-in replacement.
Claude Sonnet 4.6 → 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.
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.
0.1 extra attempts means 10 extra full attempts per 100 requests. Cache writes, tool charges, taxes and unlisted charges are excluded.
Claude Sonnet 4.6Estimated total: $13.5 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 4.6
GPT-5.6 Sol
Coverage
2,000
$13.5Lowest known
$18
All computed
4,096
$19.788Lowest known
$26.384
All computed
32,768
$105.804Lowest known
$141.072
All computed
131,072
$400.716Lowest known
$534.288
All computed
271,999
$823.497Lowest known
$1,097.996
All computed
272,000
$823.5Lowest known
$1,098
All computed
272,001
$823.503Lowest known
$2,191.008
All computed
Vary output; hold input, requests, cache and retries fixed.
Output tokens
Claude Sonnet 4.6
GPT-5.6 Sol
128
$7.92
$10.56
2,048
$36.72
$48.96
8,192
$128.88
$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.
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.
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.
Saved local decisions · 0
No version 2 decision records are stored in this browser.
Questions this page answers
Is Claude Sonnet 4.6 a better-and-cheaper replacement for GPT-5.6 Sol?
Claude Sonnet 4.6 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 overlap; this is not an established quality improvement.
Which model is higher rated: Claude Sonnet 4.6 or GPT-5.6 Sol?
Claude Sonnet 4.6 scores higher on LMArena general (1457.8 ±3.5) compared to GPT-5.6 Sol (1457.2 ±4.3), a margin of 0.6 Elo points. However, because the 95% confidence intervals overlap, this does not establish an unconditional superiority across all tasks.
Which model is more cost-effective: Claude Sonnet 4.6 or GPT-5.6 Sol?
On a standard balanced workload (3 prompt tokens per 1 generated token), Claude Sonnet 4.6 costs $6.00 per 1M tokens versus $8.00 for GPT-5.6 Sol. GPT-5.6 Sol is approximately 1.3× the price of Claude Sonnet 4.6. Base input rates are $3.00 for Claude Sonnet 4.6 and $4.00 for GPT-5.6 Sol; base output rates are $15.00 for Claude Sonnet 4.6 and $20.00 for GPT-5.6 Sol.
How do their context windows and generation limits compare?
Claude Sonnet 4.6 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 4.6 and GPT-5.6 Sol?
Switching from Claude Sonnet 4.6 to GPT-5.6 Sol causes no detected architectural capability loss. Conversely, moving from GPT-5.6 Sol to Claude Sonnet 4.6 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 4.6 or GPT-5.6 Sol be self-hosted or deployed privately?
Both Claude Sonnet 4.6 and GPT-5.6 Sol are proprietary cloud models offered via managed API endpoints. Claude Sonnet 4.6 is served by Anthropic and 9 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.
