Head-to-head
Claude Opus 4.6 vs Claude Opus 4.7: which AI model wins in 2026?
Claude Opus 4.6 ($25/1M out) and Claude Opus 4.7 ($25/1M out) are two of the most-used AI models in 2026. Across 3 community votes, Claude Opus 4.7 leads with 57% approval.
Quick verdict
On Reasoning, pick Claude Opus 4.7: the arena rates it 4.5/5 against 4/5 for Claude Opus 4.6. Both start at the same price: $25/1M out.
Line-by-line comparison
Strengths and weaknesses
Claude Opus 4.6
- 80.8% SWE-bench Verified (25-trial average) and top Terminal-Bench 2.0 score at launch, the leading agentic coding model of its generation (Feb 2026)
- First Opus with a 1M-token context window: 76% on MRCR v2 8-needle at 1M tokens vs 18.5% for Sonnet 4.5
- Large reasoning jump over Opus 4.5: ARC-AGI-2 68.8% vs 37.6%, +190 Elo on GDPval-AA economic-value tasks (~144 Elo over GPT-5.2)
- Kept Opus 4.5 pricing ($5/$25 per 1M tokens) despite the gains; full 1M context now billed at standard rates, 50% batch discount
- Adaptive thinking plus effort parameter (low/medium/high/max) to trade intelligence, latency and cost per request
- Strong autonomous agent behavior: parallelizes work and needs less handholding than Opus 4.5 (Every.to Vibe Check)
- Slower and more verbose than Opus 4.5; reviewers report the pace 'wavers under load' on long agentic runs (Every.to)
- Writing regressed: in blind tests Every.to's team preferred Opus 4.5's prose, and 4.6 shows more AI-isms like 'X not Y' constructions
- Sometimes makes unexpected changes and 'doesn't always know its own skills', requiring closer supervision than GPT-5.x Codex per reviewers
- Superseded within months by Opus 4.7 and 4.8 at the same $5/$25 price, and fast mode is not available on 4.6 since June 2026 (requests run at standard speed)
- Some devs report benchmark fatigue: day-to-day coding gains over 4.5 are harder to feel than the scores suggest, and SWE-bench itself was flat vs 4.5 (80.8% vs 80.9%)
Claude Opus 4.7
- 87.6% SWE-bench Verified (up from 80.8% on Opus 4.6) and 64.3% SWE-bench Pro at launch, ahead of GPT-5.4 (57.7%) and Gemini 3.1 Pro (54.2%)
- 1M-token context window and 128K max output at flat $5/$25 pricing with no long-context premium (300K output via Batch API beta)
- First Claude with high-resolution vision: accepts images up to 2576px on the long edge with pixel-accurate coordinates, ~3x prior detail
- Standout code review: finds more real bugs with stronger cross-file reasoning than rivals in independent tests, and 21% fewer document-reasoning errors than Opus 4.6
- Fine cost control via new xhigh effort level and Task Budgets (beta): low-effort 4.7 roughly matches medium-effort 4.6 output quality
- Recent knowledge: reliable cutoff of January 2026, the freshest of any Claude model at release
- New tokenizer inflates token counts roughly 30% for the same text versus pre-4.7 models (per Anthropic's own docs), raising effective per-request cost despite the unchanged sticker price
- Very verbose in agentic use: one benchmark found GPT-5.5 used 72% fewer output tokens on equivalent coding tasks, and reviewers call its narration over-communicative
- Breaking API changes bite migrators: temperature/top_p/top_k and thinking budget_tokens now return 400 errors, and thinking text is hidden by default
- Moderate latency with minutes-long turns at high effort; fast mode is a premium research preview already deprecated on 4.7
- Superseded by Opus 4.8 at the same $5/$25 within ~3 months, and real-time cybersecurity safeguards can false-positive on legitimate security work
Cast your verdict
One recommendation per tool per gladiator. It reshapes the crowd score everyone sees.
The arena’s verdict on Claude Opus 4.6
A clear upgrade over Opus 4.5 for agentic coding and long-context work at identical pricing, and it held the top agentic coding benchmarks at launch. In mid-2026 however there is little reason to start new projects on it: Opus 4.8 costs the same $5/$25 and outperforms it across the board, so pick 4.6 mainly to pin an already-validated behavior. Writers should avoid it, since blind tests preferred Opus 4.5's prose, and latency-sensitive users should note it is slower than 4.5 with no fast mode option.
The arena’s verdict on Claude Opus 4.7
Choose Opus 4.7 only if you are already pinned to it for reproducibility: Opus 4.8 costs the same $5/$25, keeps an identical API surface, and outperforms it, making it the better default for new projects. It remains a very strong pick for agentic coding, code review and 1M-context document work, and is a clear upgrade over Opus 4.6. Teams migrating from 4.6 should budget for breaking API changes and a tokenizer that yields roughly 30% more tokens per prompt. Cost-sensitive users should look at Sonnet 5, which delivers near-Opus quality at $3/$15 (intro $2/$10 through August 31, 2026).
What the crowd says
On Claude Opus 4.6
No verdicts yet. Be the first to speak.
On Claude Opus 4.7
“Watch your invoices. New tokenizer counts ~30% more tokens for the same text, and it narrates every tiny step. Sticker price unchanged, effective cost definitely not.”
“Came from 4.6 and stopped chunking repos entirely. 1M context, 128K output, flat $5/$25 with no long-context premium. That pricing decision alone won me over.”
“87.6 SWE-bench Verified is not just marketing, it closes tickets GPT-5.4 fumbles. And the hi-res vision with pixel-accurate coords finally makes screenshot debugging useful.”
Keep comparing
Frequently asked questions
Is Claude Opus 4.6 better than Claude Opus 4.7?
The crowd currently sides with Claude Opus 4.7: 57% recommend it, versus 50% for Claude Opus 4.6 (3 votes). On Reasoning, Claude Opus 4.7 rates higher (4.5/5 vs 4/5). 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 4.6 or Claude Opus 4.7?
They cost the same to start: both begin at $25/1M out.
How much do Claude Opus 4.6 and Claude Opus 4.7 cost per 1M tokens?
Claude Opus 4.6: $5/1M in per 1M input tokens, $25/1M out per 1M output tokens. Claude Opus 4.7: $5/1M in per 1M input tokens, $25/1M out per 1M output tokens.