Claude Sonnet 5.5 and GPT-6.1 Sol are the mid-priced strong tiers from Anthropic and OpenAI, listed at the same price per token. That makes this a comparison of capabilities, controls and ecosystems rather than cost.
Anthropic figures were re-read from its Models overview and OpenAI figures from its Models page on 2026-11-02. Both are vendor documentation; no benchmark results are used.
Key differences at a glance
- Same price: $2 / $10 per million input/output tokens.
- Context: 1M tokens (Anthropic) against 1.05M tokens (OpenAI); both list 128K output.
- Knowledge cutoff: June 2026 against April 30, 2026.
- Reasoning controls: adaptive thinking with default effort high (Anthropic) against effort levels from low through max (OpenAI, as compiled).
- Input: both document text and image input with text output.
Specification comparison
| Feature | Claude Sonnet 5.5 | GPT-6.1 Sol |
|---|---|---|
| Positioning | Best combination of speed and intelligence | Near-Astra performance for complex work at lower cost |
| Context window | 1M tokens | 1.05M tokens |
| Max output | 128K | 128K |
| Price per MTok (in / out) | $2 / $10 | $2 / $10 |
| Input modalities | Text and image | Text and image (all latest models) |
| Reliable knowledge cutoff | Jun 2026 | Apr 30, 2026 |
| Reasoning | Adaptive; default effort high | Low through max effort |
Shaded cells mean the cited sources did not state the value. We do not fill gaps from memory.
Equal list prices
At identical per-token prices, the cost difference comes from how many tokens each model uses for your tasks (including reasoning tokens), how often it needs retries, and discounts such as Anthropic's 50% Batch API reduction and cache-read pricing. Measure cost per successful task, not per token.
Capabilities and controls
Anthropic describes Sonnet 5.5 as the best combination of speed and intelligence; OpenAI describes Sol as near-Astra performance at lower cost. Anthropic's adaptive thinking is steered by an effort parameter that defaults to high for Sonnet 5.5; OpenAI's models expose reasoning effort levels. These controls are not equivalent scales, so compare outputs, not settings.
Limits and freshness
The context windows are effectively the same size (1M against 1.05M tokens) and both list 128K tokens of output. Sonnet 5.5's reliable knowledge cutoff (June 2026) is about two months newer than Sol's (April 30, 2026).
Ecosystem and privacy
Platform availability, SDKs, tool integrations and data-handling terms often decide between vendors. Anthropic lists Sonnet 5.5 on its API and on Amazon Bedrock, Google Cloud, Microsoft Foundry and Claude Platform on AWS. Neither cited page covers privacy terms; review each vendor's commercial terms.
Strengths and limitations
Claude Sonnet 5.5
Strengths
- Later stated knowledge cutoff; fast latency label.
Limitations
- No benchmark data on the page.
GPT-6.1 Sol
Strengths
- Slightly larger context window (1.05M).
Limitations
- Earlier stated cutoff; no latency label on the page.
Verified pricing
Both $2 / $10. Prices are per million tokens (MTok) as listed on the cited page on the verification date; they can change.
Which should you choose?
- Most recent knowledge: Claude Sonnet 5.5 — Jun 2026 vs Apr 2026
- Largest context: GPT-6.1 Sol — 1.05M vs 1M tokens
Our verdict
Prices and output limits match. Differences listed are minor, so evaluate both on your workload, and weigh tooling and ecosystem.
Frequently asked questions
Are Claude Sonnet 5.5 and GPT-6.1 Sol the same price?
Yes. Both list $2 per million input tokens and $10 per million output tokens on 2026-11-02.
Which has the newer knowledge cutoff?
Claude Sonnet 5.5 (June 2026) against GPT-6.1 Sol (April 30, 2026).
Which is better at coding?
Neither vendor page provides a comparable benchmark and AYORAHUB did not test them. Evaluate both on your own codebase.
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How this was checked
Specifications compiled on 2026-11-02 from the sources below. Part of the cited evidence was re-checked on 2026-11-02; see the notes below.
Both vendor pages re-read on 2026-11-02; prices, limits and cutoffs matched. OpenAI reasoning-effort row not visible in the re-read.
Disclosure: AYORAHUB did not hands-on test these products or services. Nothing on this page is a lab measurement, benchmark or review score; analysis explains what the cited specifications mean in practice.
- All Anthropic figures come from the single Models overview page; availability on cloud platforms is not stated there.
- OpenAI figures come from the Models listing page; individual model pages may add detail.
- No quality, speed or benchmark claims are made.
Sources
- Models overview — Anthropic Claude Platform Docs (manufacturer/official)
- Models — OpenAI API Docs (manufacturer/official)