Head-to-head
Claude Opus 4.8 vs GPT-5.5: which AI model wins in 2026?
Claude Opus 4.8 ($25/1M out) and GPT-5.5 ($30/1M out) are two of the most-used AI models in 2026. Across 6 community votes, Claude Opus 4.8 leads with 57% approval.
Quick verdict
On Reasoning, pick GPT-5.5: the arena rates it 5/5 against 4.5/5 for Claude Opus 4.8. On budget, Claude Opus 4.8 wins: it starts at $25/1M out versus $30/1M out for GPT-5.5.
Line-by-line comparison
Strengths and weaknesses
Claude Opus 4.8
- SWE-Bench Pro 69.2% (vs 64.3% for Opus 4.7) and beats prior Opus models on CursorBench at every effort level; strong real-world reports on large refactors and multi-file bug hunts
- About 4x less likely than Opus 4.7 to let flaws in its own generated code pass unflagged; big jump on math reasoning (USAMO 2026: 96.7% vs 69.3%)
- 1M-token context and 128K output at unchanged $5/$25 pricing, with no long-context premium; batch API at 50% off ($2.50/$12.50)
- Fast mode (research preview) delivers up to 2.5x output speed at $10/$50, 3x cheaper than Opus 4.7's fast tier ($30/$150)
- Unique API features for agents: mid-conversation system messages that preserve the prompt cache, and Dynamic Workflows spawning parallel subagents in Claude Code
- 84% on Online-Mind2Web browser automation and record score on Legal Agent Benchmark (first model past 10% all-pass); strong enterprise knowledge work (Box reports 87% vs 77% internally)
- Turn-by-turn regressions reported: missed obvious instructions in planning docs, answering a narrow slice of the goal, and worse one-shot simple UI generation than 4.7
- Writing style criticized by heavy users: excessive hedging, over-cautious editing that 'cuts anything bold or funny' (Steve Yegge), and pushback loops even against well-evidenced theses
- Language-mixing quirk: users report random Chinese, Cyrillic, or Greek insertions in long research threads
- Visible quality degradation past ~200K tokens in hands-on use despite the advertised 1M window
- Vending-Bench regression: fell for scam suppliers about 30x more than 4.7 and negotiates worse (a side effect of stricter honesty alignment)
GPT-5.5
- 1M-token context window (1,050,000) with 128K max output and reasoning effort tunable from none to xhigh
- State-of-the-art ARC-AGI-2 at 85.0% (vs 73.3% for GPT-5.4) and Terminal-Bench 2.0 at 82.7%
- Strong agentic coding autonomy: devs report it one-shots tasks that took GPT-5.4 multiple turns and fixes its own mistakes; +50 points on Code Arena vs GPT-5.4
- Aggressive discounts: 90% off cached input ($0.50/1M) and 50% off via Batch or Flex ($2.50/$15)
- Fast for a frontier reasoner: devs say it is the first GPT model comfortable to run at medium or low thinking effort
- List price doubled vs GPT-5.4 ($5/$30 vs $2.50/$15) for the same 1M-token context window
- Overly literal instruction-following: devs report it fails to infer intent in obvious places where Claude succeeds
- Trails Claude Opus 4.8 on SWE-bench Pro (58.6% vs 69.2%); HN developers still favor Claude roughly 2:1 for coding
- Sometimes too conservative with code changes or skips deep reasoning entirely, answering immediately on complex prompts
- Long-context surcharge: prompts over 272K input tokens are billed 2x input and 1.5x output for the whole session
Cast your verdict
One recommendation per tool per gladiator. It reshapes the crowd score everyone sees.
The arena’s verdict on Claude Opus 4.8
A drop-in upgrade for Opus 4.7 users: identical API surface and $5/$25 pricing with real gains on long-horizon agentic coding, code review, and enterprise analysis. Choose it if you run Claude Code, multi-file migrations, security audits, or agent pipelines that inspect, act, and verify over many steps. Skip it for quick one-shot UI snippets or prompts tightly tuned to 4.7 behavior, where users report regressions, and pick Sonnet 5 ($3/$15, intro $2/$10 through Aug 2026) if cost matters more than ceiling capability. Writers sensitive to hedging and over-cautious editing may find its style frustrating.
The arena’s verdict on GPT-5.5
Pick GPT-5.5 over GPT-5.4 if you need stronger agentic autonomy, terminal-heavy workflows, or SOTA abstract reasoning, but know the list price doubled from GPT-5.4's $2.50/$15 to $5/$30 while the 1M-token context stayed the same. Teams doing high-stakes multi-file refactoring may still prefer Claude Opus, which leads SWE-bench Pro (69.2% vs 58.6%) and infers intent better from loose prompts. Budget-sensitive users should mind the 272K-token surcharge and reports of faster limit burn, and lean on caching, Batch, or Flex to halve costs.
What the crowd says
On Claude Opus 4.8
“Writing took a hit. It hedges everything and edits any bold or funny line out of my drafts. Also caught it answering a narrow slice of my planning doc and calling it done.”
“Threw USAMO-level math at it for a lark and it just grinds through. 96.7 vs 69 for 4.7 tracks with what I see. Same $5/$25, 1M context, no excuse not to switch.”
“Upgraded from 4.7 for a monorepo refactor and the difference is real. It actually flags its own sketchy code instead of shipping it. Multi-file bug hunts feel way less babysat.”
On GPT-5.5
“It is painfully literal. Where Claude infers intent in obvious places, 5.5 wants everything spelled out. And the price doubled vs 5.4 for the same 1M context.”
“85 on ARC-AGI-2 and you can feel it. Stuff that used to stall my agent just resolves now. 1M context with 128K output covers every workflow I have.”
“5.5 one-shots tasks that took 5.4 three turns, and it fixes its own mistakes mid-run instead of doubling down. The reasoning effort dial from none to xhigh is genuinely useful.”
Keep comparing
Frequently asked questions
Is Claude Opus 4.8 better than GPT-5.5?
On Reasoning, GPT-5.5 rates higher (5/5 vs 4.5/5). The right pick depends on your use case. The line-by-line comparison on this page breaks down pricing, key specs and arena ratings.
Which is cheaper, Claude Opus 4.8 or GPT-5.5?
Claude Opus 4.8 is cheaper: it starts at $25/1M out, while GPT-5.5 starts at $30/1M out.
How much do Claude Opus 4.8 and GPT-5.5 cost per 1M tokens?
Claude Opus 4.8: $5/1M in per 1M input tokens, $25/1M out per 1M output tokens. GPT-5.5: $5/1M in per 1M input tokens, $30/1M out per 1M output tokens.