Claude Opus 4.8 is the stronger coding model by every public benchmark: 69.2% SWE-Bench Pro vs GPT-5.5's 58.6%, and 1890 Arena Elo vs 1769 — a 67% head-to-head win rate. Pricing is tied at $5/$25 per 1M tokens. GPT-5.5 is the better pick when your stack is already OpenAI-native (Codex, computer-use, OpenAI APIs). For new integrations focused on coding quality, Opus 4.8 is the clear choice.
AnthropicPremium
Claude Opus 4.8
Best value premium coder — frontier-grade at half of Fable 5's price.
Winner
VS
OpenAIPremium
GPT-5.5
Best OpenAI flagship for agentic coding, research, and computer-use work.
At a glance
Claude Opus 4.8
GPT-5.5
Input cost / 1M tokens
$$5.00/1M
$$5.00/1M
Output cost / 1M tokens
$$25.00/1M
$$30.00/1M
Context window
1M tokens
1M tokens
Speed
Deliberate
Balanced
Price tier
Premium
Premium
Benchmarks
SWE-bench (coding)
88.6%
—
Arena Elo
1,890
—
MMLU
93%
—
How they compare
Which model wins for each use case — and why.
Coding ceilingClaude Opus 4.8 wins
Claude Opus 4.8 scores 69.2% on SWE-Bench Pro vs GPT-5.5's 58.6% — a 10.6-point lead, the largest gap between any two frontier coding models right now.
Agentic workflowsClaude Opus 4.8 wins
Opus 4.8 introduces native parallel subagents, letting it spawn, coordinate, and merge multi-agent task results in a single orchestrated call.
OpenAI ecosystemGPT-5.5 wins
GPT-5.5 is the right call when you need Codex, ChatGPT, OpenAI APIs, or computer-use workflows built on OpenAI tooling.
PriceTie
Both models are priced at $5/1M input and $25/1M output — no cost advantage either way.
Context windowTie
Both support a 1M token API context window.
Arena EloClaude Opus 4.8 wins
Claude Opus 4.8 scores 1890 on GDPval-AA vs GPT-5.5 at 1769 — implying about a 67% head-to-head win rate in human preference.
Which should you pick?
Pick Claude Opus 4.8 if…
You want the highest current public coding benchmark score (69.2% SWE-Bench Pro)
You are running autonomous PR review, multi-file refactors, or high-stakes engineering agents
You want native parallel subagents without building your own orchestration layer
You are starting a new integration and want the best model at this price tier
For most workflows, Claude Opus 4.8 is the stronger choice.
The best value at the premium tier now that Claude Fable 5 leads on raw capability. 69.2% SWE-Bench Pro, 1890 Elo, and built-in parallel subagents at $5/$25 — half the price of Fable 5. The smart default for serious coding when you don't need the absolute frontier.
The case for each model
What each one is genuinely good at, where it falls down, and when we would steer you away from it.
Our overall pick in this comparison. Against GPT-5.5 it costs about 14% less per token.
Anthropic's newest Opus flagship — 69.2% SWE-Bench Pro, 88.6% SWE-Bench Verified, 1890 Arena Elo (121 pts ahead of GPT-5.5), and native parallel subagents. Same $5/$25 price as Opus 4.7.
Input
$5.00/1M
Output
$25.00/1M
Context
1M tokens
Speed
Deliberate
What people actually use it for
Running parallel subagent workflows that split, solve, and merge complex engineering tasks
Autonomous PR review and multi-file refactors where accuracy matters more than speed
Deep research synthesis across 1M-token corpora — patents, codebases, legal documents
Where it wins
69.2% SWE-Bench Pro — new #1, up from Opus 4.7's 64.3%
88.6% SWE-Bench Verified and 83.4% OSWorld computer use
Native parallel subagents: orchestrated multi-agent execution in a single call
1890 Arena Elo, 121 points ahead of GPT-5.5
Where it falls down
Deliberate pace — not the right pick for latency-sensitive applications
Same price tier as Opus 4.7; not a budget option
Skip it if
You need low-latency responses, image generation, or a workflow locked to OpenAI tooling.
Our verdict
The best value at the premium tier now that Claude Fable 5 leads on raw capability. 69.2% SWE-Bench Pro, 1890 Elo, and built-in parallel subagents at $5/$25 — half the price of Fable 5. The smart default for serious coding when you don't need the absolute frontier.
The runner-up here, but not by a wide margin. Against Claude Opus 4.8 it costs about 14% more per token and answers faster.
OpenAI's latest agentic flagship for coding, research, computer-use workflows, and long multi-step knowledge work.
Input
$5.00/1M
Output
$30.00/1M
Context
1M tokens
Speed
Balanced
What people actually use it for
Running multi-file implementation and debugging loops in Codex
Building agents that research, operate tools, and verify work over long tasks
Analyzing large business, scientific, or technical documents with 1M context
Where it wins
58.6% on SWE-Bench Pro, ahead of GPT-5.4 on the same public coding benchmark
82.7% on Terminal-Bench 2.0 for complex command-line workflows
1M token API context window for large-codebase and document-heavy workflows
Where it falls down
Claude Opus 4.7 leads GPT-5.5 on SWE-Bench Pro for pure coding ceiling
Premium API pricing makes it less attractive for high-volume low-risk work
Skip it if
You only care about the highest public coding benchmark score or need a cheaper high-volume model.
Our verdict
The strongest OpenAI pick for agentic coding and knowledge work. Claude Opus 4.7 still wins on the public SWE-Bench Pro coding number, but GPT-5.5 is the better OpenAI default when ecosystem, Codex, or computer-use workflows matter.
Full pricing, benchmark table and release notes on the GPT-5.5 page.
Frequently asked questions
Is Claude Opus 4.8 or GPT-5.5 better for coding?
Claude Opus 4.8 is better by public benchmarks: 69.2% SWE-Bench Pro vs GPT-5.5's 58.6%. That is a 10+ point gap — the largest difference between any two frontier coding models currently available.
Is Claude Opus 4.8 more expensive than GPT-5.5?
No. Both are priced at $5 per million input tokens and $25 per million output tokens. There is no price difference between them.
What are Claude Opus 4.8's parallel subagents?
Opus 4.8 can spin up multiple subagents inside a single API call. An orchestrator breaks a task into parts, each subagent solves its portion independently, and the orchestrator merges results. This removes the need to build your own multi-agent loop.
When should I choose GPT-5.5 instead of Opus 4.8?
Choose GPT-5.5 when your stack is already OpenAI-native: Codex integrations, ChatGPT rollout, OpenAI function-calling agents, or computer-use workflows that depend on OpenAI's tooling.
How does Claude Opus 4.8 compare to Opus 4.7?
Opus 4.8 improves SWE-Bench Pro from 64.3% to 69.2%, adds parallel subagents, and improves Arena Elo by roughly 90 points — all at the same $5/$25 price. It is a straightforward upgrade for new deployments.