Claude Opus 5 vs GPT-5.6 Sol
The listed rates and 1M-input + 1M-output workload example use base tiers, assuming every request meets: openai/gpt-5.6-sol: request input ≤ 272,000 tokens. Requests above a threshold use the long-context rates below. GPT-5.6 Sol is the lower-priced of the two on Router One — about 67% less on a 1M-input + 1M-output mix. Both carry a 1.05M context window. Claude Opus 5 answers on /v1/chat/completions and /v1/messages (Claude Code); GPT-5.6 Sol on /v1/chat/completions and /v1/responses (Codex CLI).
Claude Opus 5 and GPT-5.6 Sol compared on current per-token rates, context window, and capabilities — both callable through one OpenAI-compatible endpoint with per-request cost traces.
Claude Opus 5 vs GPT-5.6 Sol: rates, context window, and capabilities
| Spec | Claude Opus 5 | GPT-5.6 Sol |
|---|---|---|
| Input / 1M tokens | $2.25 | $0.50 |
| Output / 1M tokens | $11.25 | $4.00 |
| Cached input / 1M tokens | $0.375 | $0.25 |
| Context window | 1.05M | 1.05M |
| Capabilities | Chat, Streaming, Tool calling, Vision | Chat, Streaming, Tool calling, Vision |
| Detail page | Claude Opus 5 | GPT-5.6 Sol |
openai/gpt-5.6-sol: request input ≤ 272,000 tokens: Input $0.50 / 1M tokens, Output $4.00 / 1M tokens, Cache write $0.50 / 1M tokens, Cached input $0.25 / 1M tokens; request input > 272,000 tokens: Input $1.00 / 1M tokens, Output $4.50 / 1M tokens, Cache write $6.25 / 1M tokens, Cached input $0.50 / 1M tokens. The total input tokens in each request select the tier; its rates apply to the whole request, not only tokens above the threshold.
What does 1M tokens cost on Claude Opus 5 vs GPT-5.6 Sol?
The listed rates and 1M-input + 1M-output workload example use base tiers, assuming every request meets: openai/gpt-5.6-sol: request input ≤ 272,000 tokens. Requests above a threshold use the long-context rates below. For a workload of 1M input plus 1M output tokens at current rates: Claude Opus 5 comes to $13.50, GPT-5.6 Sol comes to $4.50 — GPT-5.6 Sol is about 67% cheaper on this mix. Real workloads skew heavily toward input tokens, so weigh the input rate by your own ratio; the cached-input row above is the posted catalog rate for that model.
Switch between Claude Opus 5 and GPT-5.6 Sol without changing code
Both models are behind the same OpenAI-compatible endpoint, so an A/B test is a one-string change — same key, same code, and every request traced with tokens, cost, and latency in the dashboard:
curl https://api.router.one/v1/chat/completions \
-H "Authorization: Bearer sk-your-router-one-key" \
-H "Content-Type: application/json" \
-d '{"model": "anthropic/claude-opus-5", "messages": [{"role": "user", "content": "Hello"}]}'
# Same request, other model — change one string:
# "model": "openai/gpt-5.6-sol"FAQ
Is Claude Opus 5 cheaper than GPT-5.6 Sol?
The listed rates and 1M-input + 1M-output workload example use base tiers, assuming every request meets: openai/gpt-5.6-sol: request input ≤ 272,000 tokens. Requests above a threshold use the long-context rates below. Input: Claude Opus 5 $2.25 vs GPT-5.6 Sol $0.50 / 1M tokens; GPT-5.6 Sol has the lower rate. Output: Claude Opus 5 $11.25 vs GPT-5.6 Sol $4.00 / 1M tokens; GPT-5.6 Sol has the lower rate. Total cost depends on the workload's input, output and cache usage. openai/gpt-5.6-sol: request input ≤ 272,000 tokens: Input $0.50 / 1M tokens, Output $4.00 / 1M tokens, Cache write $0.50 / 1M tokens, Cached input $0.25 / 1M tokens; request input > 272,000 tokens: Input $1.00 / 1M tokens, Output $4.50 / 1M tokens, Cache write $6.25 / 1M tokens, Cached input $0.50 / 1M tokens. The total input tokens in each request select the tier; its rates apply to the whole request, not only tokens above the threshold. Rates change; the /models page is the live source of truth.
Can I switch between Claude Opus 5 and GPT-5.6 Sol without changing code?
Yes. Both are served through the same OpenAI-compatible endpoint, so switching is changing the model string in the request — the key, base URL, and request shape stay identical.
Where do these numbers come from?
Specs and prices on this page render from the live Router One catalog — the same data as the /models page — and refresh with it. Pricing methodology is documented on /pricing-methodology. Rates on this page were read from the live catalog on 2026-09-15 (UTC) and refresh within the hour.