Model comparison · accepted catalogue facts 2026-10-21
Claude Opus 4.7 vs GPT-5.6 Sol
Neither model has both an equal-or-higher measured score and an equal-or-lower estimated price in this pair. Retaining your current model is a valid outcome.
Editorial comparison: Cross-provider head-to-head: Claude Opus 4.7 (Anthropic) vs GPT-5.6 Sol (OpenAI) on intelligence, speed, and pricing Inclusion does not recommend either model.
Balanced effective USD / 1M tokens · lower is better
$8.00/M
In-Depth Analysis
Claude Opus 4.7 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 Opus 4.7 leads by 32.5 Elo
Claude Opus 4.7: 1489.7 ±3.75 · 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 Opus 4.7
GPT-5.6 Sol
Cost Difference
Advantage
Balanced3 tokens in per 1 out
$10.00/1M tokens
$8.00/1M tokens
$2.00(20% diff)
GPT-5.6 Sol costs less
SummariseHuge input, tiny output
$4.72/1M tokens
$3.77/1M tokens
$0.944(20% diff)
GPT-5.6 Sol costs less
ChatLong cached system prompt
$11.65/1M tokens
$9.32/1M tokens
$2.33(20% diff)
GPT-5.6 Sol costs less
Code genOutput dominates
$16.64/1M tokens
$13.31/1M tokens
$3.33(20% diff)
GPT-5.6 Sol costs less
AgenticContext replayed each turn
$5.32/1M tokens
$4.26/1M tokens
$1.06(20% diff)
GPT-5.6 Sol costs less
Architectural & Operational Specifications
Specification
Claude Opus 4.7
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
$5.00 / 1M tokens
$4.00 / 1M tokens
GPT-5.6 Sol input rate is cheaper
Base output price
$25.00 / 1M tokens
$20.00 / 1M tokens
GPT-5.6 Sol output rate is cheaper
Cached input price
$0.500 / 1M tokens
$0.400 / 1M tokens
GPT-5.6 Sol 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 · 8 provider offers
OpenAI · 7 provider offers (2.2× spread)
—
When to Choose Claude Opus 4.7
Higher measured general capability (1489.7 Elo on human evaluation).
Direct integration with Anthropic tooling and API features.
Risks when moving from GPT-5.6 Sol → Claude Opus 4.7:
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
Neither model has both an equal-or-higher measured score and an equal-or-lower estimated price in this pair. Retaining your current model is a valid outcome.
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 Opus 4.7 · 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 Opus 4.7 is a valid decision. No pairwise comparison certifies a drop-in replacement.
Claude Opus 4.7 → 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 Opus 4.7Estimated total: $22.5 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 Opus 4.7
GPT-5.6 Sol
Coverage
2,000
$22.5
$18Lowest known
All computed
4,096
$32.98
$26.384Lowest known
All computed
32,768
$176.34
$141.072Lowest known
All computed
131,072
$667.86
$534.288Lowest known
All computed
271,999
$1,372.495
$1,097.996Lowest known
All computed
272,000
$1,372.5
$1,098Lowest known
All computed
272,001
$1,372.505Lowest known
$2,191.008
All computed
Vary output; hold input, requests, cache and retries fixed.
Output tokens
Claude Opus 4.7
GPT-5.6 Sol
128
$13.2
$10.56
2,048
$61.2
$48.96
8,192
$214.8
$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 Opus 4.7 a better-and-cheaper replacement for GPT-5.6 Sol?
Neither model has both an equal-or-higher measured score and an equal-or-lower estimated price in this pair. Retaining your current model is a valid outcome.
Which model is higher rated: Claude Opus 4.7 or GPT-5.6 Sol?
Claude Opus 4.7 scores higher on LMArena general (1489.7 ±3.8) compared to GPT-5.6 Sol (1457.2 ±4.3), a margin of 32.5 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 Opus 4.7 or GPT-5.6 Sol?
On a standard balanced workload (3 prompt tokens per 1 generated token), GPT-5.6 Sol costs $8.00 per 1M tokens versus $10.00 for Claude Opus 4.7. Claude Opus 4.7 is approximately 1.3× the price of GPT-5.6 Sol. Base input rates are $5.00 for Claude Opus 4.7 and $4.00 for GPT-5.6 Sol; base output rates are $25.00 for Claude Opus 4.7 and $20.00 for GPT-5.6 Sol.
How do their context windows and generation limits compare?
Claude Opus 4.7 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 Opus 4.7 and GPT-5.6 Sol?
Switching from Claude Opus 4.7 to GPT-5.6 Sol causes no detected architectural capability loss. Conversely, moving from GPT-5.6 Sol to Claude Opus 4.7 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 Opus 4.7 or GPT-5.6 Sol be self-hosted or deployed privately?
Both Claude Opus 4.7 and GPT-5.6 Sol are proprietary cloud models offered via managed API endpoints. Claude Opus 4.7 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.
