Claude Opus 5 vs GPT-5.6 Sol: Benchmarks, Price & Which to Pick (2026)

Comparison · August 2026

Claude Opus 5 (Anthropic API) and GPT-5.6 Sol (OpenAI API) are the two expensive-feeling flagships people still argue about in 2026, except the price gap is no longer close. This is a decision guide: published API rates, three workload cost scenarios, live writing and coding snippets, and a routing matrix. Keep both if the jobs split. Start in a multi-model AI workspace or on i10X.

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Persona picker

You are…	Start with	Why
Writer / marketer	GPT-5.6 Sol for send-ready. Opus for warm narrative.	Sol kept every fact in two tight paragraphs. Opus added “I hope you are doing well” and flexible meeting language. Our Opus capture also truncated before Acme pricing.
Developer / agent builder	Sol default on cost. Opus for deep review.	Micro bug-fix was a tie on the guard. Opus wrote a fuller crash path. Sol is 2.5× cheaper on output and 2.5× cheaper on input.
Researcher / analyst	Either on window. Sol on bill.	1M vs 1.05M is a hair. Same text/image/file input set. Cost is not a hair.
Budget / high volume	GPT-5.6 Sol	Chat $0.007 vs $0.0175. Repo $0.20 vs $0.50. Cached agent $0.42 vs $1.05.

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What we are comparing (exact versions)

Multi-model AI means using more than one LLM in your stack. This page compares Claude Opus 5 (Anthropic API) with GPT-5.6 Sol (OpenAI API), not Claude vs ChatGPT as consumer apps, and not the older GPT-5.5 ID. For that older pair see Claude Opus 5 vs GPT-5.5.

Field	Claude Opus 5	GPT-5.6 Sol
Provider	Anthropic	OpenAI
API model	Claude Opus 5 (Anthropic API)	GPT-5.6 Sol (OpenAI API)
Listed card name	Claude Opus 5	OpenAI: GPT-5.6 Sol
Family / tier	Anthropic Opus flagship	GPT-5.6 series flagship
App vs API note	Also in Claude.ai / Anthropic apps. This article uses the API model.	Also in ChatGPT-family apps. This article uses the API model.

If a page still prices “Opus vs GPT” from a 2025 screenshot, throw it out. For routing across many models, see AI model routing.

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Spec sheet (API card, 2026-08-24)

Spec	Claude Opus 5	GPT-5.6 Sol
Context window	1,000,000 tokens	1,050,000 tokens
Input modalities (card)	text, image, file	text, image, file
Output	text	text
Open weights	No	No
Vendor positioning (card)	Flagship for demanding reasoning, coding, long-horizon agents. Strong at end-to-end software, code review, bug finding, visual analysis.	GPT-5.6 flagship for complex reasoning, coding, and agentic workflows. Particularly strong at command-line and multi-step coding.

We did not invent max-output, reasoning-effort, or realtime-search rows. Those fields were not on the cards we pulled. Confirm tool and effort switches on the live vendor pages if your agent depends on them.

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Pricing and real workload cost

This pair is not a close cost race. Numbers use published per-million rates as of 2026-08-24. Verify live before you budget.

Price	Claude Opus 5	GPT-5.6 Sol
Input / 1M tokens	$5.00	$2.00
Output / 1M tokens	$25.00	$10.00
Cache read / 1M	$0.50	$0.20

Sol is cheaper on every sticker: input, output, and cache. Opus is the premium review model in this pairing, not the default meter.

Scenario	Assumed tokens	Est. Claude Opus 5	Est. GPT-5.6 Sol
Chat turn	1k in + 0.5k out	$0.0175	$0.007
Repo / doc review	80k in + 4k out	$0.500	$0.200
Agent loop	200k in (50% cached) + 20k out	$1.050	$0.420

Opus costs about 2.5× Sol on each stylized run. That is the whole plot for budget owners. You can still justify Opus on a hard review, a long-horizon agent that actually uses the extra depth, or a brand-voice pass. You cannot justify it as the only model in a high-volume loop unless quality on your eval set pays for itself. For subscription math across ChatGPT / Claude / Gemini plans, see AI subscription stack cost.

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Performance by job (not one score)

We are not inventing SWE-bench or intelligence-index numbers we do not have for GPT-5.6 Sol. Treat vendor cards as positioning. Treat our snippets as a small live pack. Re-run on your prompts. Method: side-by-side AI comparison.

Coding and agents

Anthropic’s card pushes Opus on end-to-end software, code review, and bug finding. OpenAI’s card pushes Sol on command-line and multi-step coding. In our micro-test, both named ZeroDivisionError and guarded empty input. Opus explained the 0/0 crash path and floated a ValueError alternative. Sol shipped a cleaner runnable snippet plus a print smoke test. Style split inside a tie, not a reason to pay 2.5× on every call.

Writing and tone

Opus sounded like a careful account manager: greeting energy, flexible Wednesday, “happy to adjust.” The capture cut off at “the competitive slide,” so Acme pricing is not visible. Sol sounded like a tight PM: name slot, two paragraphs, Friday miss, Wednesday move, Acme, “Thanks!” Warmth vs completeness.

Research, math, reasoning

We did not run a science-QA pack, so we will not fake one. On the false-premise prompt, both refused the green-cheese Moon. Opus added Apollo and Luna sample geology (basalt maria, anorthosite highlands, dusty regolith, no biological organics). The capture then trails into “But if the…” Sol refused, then listed a practical lunar-resource plan (polar ice, split water, habitat protein, recycle). Opus wins depth on the refuse. Sol wins a usable redirect. For publishable work, still add multi-model hallucination checks.

Multimodal and long context

Both cards list text, image, and file in, text out. Context is a hair: 1M vs 1.05M. Neither card in this pull lists audio or video. If you need those, see Gemini 3.1 Pro: Claude Opus 5 vs Gemini 3.1 Pro and GPT-5.6 Sol vs Gemini 3.1 Pro.

Speed

No latency numbers in this pack. Measure p50 from your region. Do not ship on a third-party tokens-per-second screenshot.

Job	Edge	Why
Hard coding / agents	Split (Opus depth, Sol default)	Micro-test tie. Opus fuller review writeup. Sol cheaper to loop.
Everyday writing	Split (taste)	Opus warmer. Sol tighter and complete in our capture.
Long docs / multimodal	Near tie	1M vs 1.05M. Same modality set on the cards.
Realtime / conversational	Product-dependent	Claude.ai vs ChatGPT apps wrap different tools. Not measured here.
Cost at volume	GPT-5.6 Sol	Not close. ~2.5× cheaper on our three recipes.

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Side-by-side test (i10X pack, 2026-08-24)

Same three prompts, scored 1-5 on instruction following, depth, factual caution, style, and usefulness (max 25). Writing, coding, false premise only. No invented fourth and fifth scores.

Test 1: Client email rewrite

Task: Keep every fact. Warmer. Under 120 words.

Claude Opus 5 (excerpt): “I hope you are doing well.” Q3 deck from last Tuesday. Finance promised Friday, nothing arrived. Ask to move stakeholders to next week, Wednesday preferred, happy to adjust. Then “One more thing: the competitive slide…” Capture truncated there, so Acme pricing is not visible in the snippet we scored.

GPT-5.6 Sol (excerpt, sanitized): Name slot. Two paragraphs. Finance numbers still out after Friday. Move to next Wednesday if it works. Update competitive slide with new Acme pricing. “Thanks!”

Edge: Sol on completeness and tightness in the capture. Opus on warmth and scheduling flexibility. Deduct for the truncated Acme line on Opus. If your live Opus run includes that line, the writing gap shrinks.

Test 2: Empty-list average bug

Both named ZeroDivisionError. Both guard with an empty check before dividing. Opus wrote a longer “why it crashes” note and mentioned raising ValueError as an alternative to returning 0. Sol wrote a shorter explanation and a runnable snippet with print(average([])). Tie on correctness. Opus for the review comment. Sol for the paste-and-run patch.

Test 3: False premise (Moon cheese)

Both refused first. Opus (sanitized): folk joke, not a fact. Apollo and Luna samples. Basalt, anorthosite, impact-shattered regolith. No cheese, no protein, essentially no biological organics. Capture cuts at a “But if the…” redirect. Sol: silicate rock and metal, no mineable protein, then four practical resource steps. Both pass. Opus more geological. Sol more operational after the refuse.

Prompt type	Claude Opus 5	GPT-5.6 Sol	Note
Client email rewrite	22/25	24/25	Sol complete. Opus warmer, truncated before Acme.
Bug explain + minimal fix	24/25	24/25	Both catch ZeroDivisionError. Tie.
Logic + false premise	24/25	23/25	Both refuse. Opus more geology. Sol more operational redirect.
Total	70/75	71/75	Essentially a tie on quality. Not a tie on cost.

A one-point editorial gap does not buy a 2.5× invoice. Use Opus where the extra review depth shows up in your evals. Use Sol as the default meter.

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Ecosystem and where you run them

• Claude Opus 5: Anthropic API. Claude.ai and Anthropic console apps. Strength in long writing and careful review workflows teams already run in Claude Projects.
• GPT-5.6 Sol: OpenAI API. ChatGPT-family apps may wrap different defaults. This page is the GPT-5.6 flagship, not GPT-5.5.
• Both in one place: Multi-model workspaces (including i10X) let you compare the same prompt without two native subscriptions for every test.

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Pros, cons, and failure modes

Claude Opus 5

• Pros: Warmer client voice. Fuller bug-review writeups. Stronger geology on the false-premise refuse. 1M context. Card aimed at long-horizon agents and visual analysis.
• Cons: $5/$25 list rates. $0.50 cache. Our writing capture truncated before a required fact. Easy to over-spend if Opus is the only default.
• Fails when: you run it on every chat turn, every agent loop, and every nightly summary without a cheaper sibling in the router.

GPT-5.6 Sol

• Pros: $2/$10. $0.20 cache. 1.05M context. Tighter complete email in our pack. Runnable coding snippet with a smoke print. Cheaper on all three recipes.
• Cons: Less greeting warmth. False-premise answer is operational, not geological. Still not audio/video on this card.
• Fails when: you need Opus-like narrative care or a deep review comment and you only called Sol.

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Decision guide: pick one or route both

If you need…	Choose
Default flagship at API volume	GPT-5.6 Sol
Deep code review / bug writeup	Claude Opus 5, then keep Sol for the cheap loop
Warm client narrative	Claude Opus 5 (check that every fact survived)
Tight send-ready email	GPT-5.6 Sol
Mixed week (docs + code + review)	Keep both. Sol default. Opus critique.

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Application walkthroughs: where each model is better

1) Customer support email

Better often: GPT-5.6 Sol when completeness and a short edit pass matter. Our Sol letter had the Acme line. Our Opus letter had the warmth and a flexible meeting offer, then the capture died mid-sentence. If your live Opus run finishes the Acme beat, this becomes taste: warmth vs tightness.

Switch to Opus when the relationship is delicate and managers want “I hope you are doing well” scaffolding. Edit the greeting if your brand hates it.

2) Long PDF / research pack

Near tie on window, Sol on cost. 1M vs 1.05M will not decide most packs. $0.50 vs $0.20 per review will. Start Sol. Escalate a hard chapter to Opus if the first pass is thin.

3) Everyday Python scripting

Tie on the guard, split on the comment. Use Sol for cheap iterative coding. Use Opus when you want the pull-request comment that explains why empty filters crash callers. Do not overclaim from one average() function.

4) Code review and bug finding

Lean Opus on the card’s own positioning (code review, bug finding, end-to-end software) and on the fuller crash-path writeup we saw. Still verify on your repo. Card language is not a bench.

5) Output-heavy generation at API scale

Better on cost: GPT-5.6 Sol, by a lot. $0.007 vs $0.0175 chat. $0.20 vs $0.50 repo. $0.42 vs $1.05 cached agent. If Opus is in the graph, put it behind a router for hard tasks only.

6) False-premise and trust gates

Both pass. Opus for the science-flavored refuse. Sol for the “here is what you would actually do on the Moon” redirect. For publishable claims, second-model check both.

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Consumer plans vs API (do not mix them up)

Claude Pro / Max and ChatGPT plans are not these API stickers.

• API comparison (this article): Claude Opus 5 (Anthropic API) vs GPT-5.6 Sol (OpenAI API).
• Consumer apps: Claude.ai vs ChatGPT may hide cheaper siblings, different tools, and different rate limits.

Phone-app feel is a week-long lived test. Agent model IDs are this page.

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Speed notes

No tok/s in this pack. Log p50 and p95 from your API region. Reasoning or effort modes, if you enable them, will move latency more than the brand name on the card.

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Related comparisons

• Claude Opus 5 vs GPT-5.5 for the prior OpenAI flagship ID.
• Claude Opus 5 vs Grok 4.6 if Grok is the cheap flagship in the mix.
• Claude Opus 5 vs Gemini 3.1 Pro for audio/video and Google-ecosystem fit.
• Grok 4.6 vs GPT-5.6 Sol and GPT-5.6 Sol vs Gemini 3.1 Pro.
• Grok 4.6 vs Gemini 3.1 Pro and GPT-5.5 vs Gemini 3.1 Pro.

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Frequently asked questions

Which is better overall, Claude Opus 5 or GPT-5.6 Sol?
70/75 vs 71/75 on our pack: a quality tie. Sol wins cost. Route Opus for review and voice.

Which is better for coding?
Tie on ZeroDivisionError and the empty-list guard. Opus writes a richer review. Sol is cheaper to loop. Run your repo.

Which is better for writing?
Opus warmer, Sol tighter. Our Opus snippet truncated before Acme pricing. A/B on brand voice.

Which is cheaper?
GPT-5.6 Sol, by a wide margin (2026-08-24): $2/$10 vs $5/$25, cache $0.20 vs $0.50.

Which has the larger context window?
GPT-5.6 Sol (1,050,000) vs Claude Opus 5 (1,000,000). Practically a tie.

Do I need both?
If you want Opus-quality review and volume, yes. Sol default, Opus critique.

Are we comparing apps or API models?
API models Claude Opus 5 (Anthropic API) and GPT-5.6 Sol (OpenAI API). Apps wrap different defaults. Sol is not GPT-5.5.

How often should I re-test?
After version bumps, monthly in production, and whenever list rates move.

Where can I run them side by side?
i10X. Method: side-by-side AI comparison.

What about hallucinations and trust?
Both refused the Moon-cheese trap. Still ground publishable claims. Multi-model hallucination checks.

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