Claude Opus 4.6 vs LongCat-2.5
Anthropic · US | Meituan · China · Updated June 2026
Quick verdict
Pick Claude Opus 4.6 for agentic coding and debugging in large codebases or long-running, multi-step autonomous agent tasks. Pick LongCat-2.5 for native multimodal upgrade to longcat-2.0 - 1.6t total parameters, about 48b active per token or limited-time api price of $0.30/$1.20 per million tokens (cached input $0.006). On a tight budget at scale, LongCat-2.5 is the value pick.
Claude Opus 4.6 (Anthropic, US) and LongCat-2.5 (Meituan, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. Claude Opus 4.6 is anthropic's February 2026 flagship Opus and the first Opus-class model with a 1M-token context window, built for agentic coding and long-running professional tasks. LongCat-2.5 is meituan's November 2, 2026 natively multimodal successor to LongCat-2.0 - 1.6T parameters and 1M context at $0.30/$1.20, with open weights planned but undated. Their biggest split is price, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Price: LongCat-2.5 is about 17× cheaper on input ($0.3/$1.2 per 1M tokens vs $5/$25 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: both advertise 1M (~1,500 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: LongCat-2.5 is the newer model by about 9 months (released November 2, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Claude Opus 4.6 | LongCat-2.5 |
|---|---|---|
| Provider | Anthropic (US) | Meituan (China) |
| Released | February 5, 2026 | November 2, 2026 |
| Context window | 1M (~1,500 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $5/$25 per 1M tokens | $0.3/$1.2 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image, code | text, image, code |
| SWE-Bench Verified | 80.8% | Not published |
| MRCR v2 @ 1M | 76% | Not published |
Who wins what
Agentic coding and debugging in large codebases
Claude Opus 4.6
Claude Opus 4.6 lists agentic coding and debugging in large codebases among its strengths; LongCat-2.5 does not.
Long-running, multi-step autonomous agent tasks
Claude Opus 4.6
Claude Opus 4.6 lists long-running, multi-step autonomous agent tasks among its strengths; LongCat-2.5 does not.
Frontier multidisciplinary reasoning (leads Humanity's Last Exam)
Claude Opus 4.6
Claude Opus 4.6 lists frontier multidisciplinary reasoning (leads Humanity's Last Exam) among its strengths; LongCat-2.5 does not.
Native multimodal upgrade to LongCat-2.0 - 1.6T total parameters, about 48B active per token
LongCat-2.5
Claude Opus 4.6 is comparatively weak here — top-tier per-token price, and its 1M-token context shipped as beta
Limited-time API price of $0.30/$1.20 per million tokens (cached input $0.006)
LongCat-2.5
At $0.3/$1.2 per 1M tokens it undercuts Claude Opus 4.6 ($5/$25 per 1M tokens), and that gap compounds at volume.
Meituan-reported Terminal-Bench v2.1 of 88.4, up from 70.8 for LongCat-2.0
LongCat-2.5
Meituan's November 2, 2026 natively multimodal successor to LongCat-2.0 - 1.6T parameters and 1M context at $0.30/$1.20, with open weights planned but undated — and it runs cheaper at $0.3/$1.2 per 1M tokens.
Lowest cost at scale
LongCat-2.5
At $0.3/$1.2 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ LongCat-2.5
At $0.3/$1.2 per 1M tokens it undercuts Claude Opus 4.6, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is agentic coding and debugging in large codebases
→ Claude Opus 4.6
It is specifically built for that.
Anyone whose priority is native multimodal upgrade to longcat-2.0 - 1.6t total parameters, about 48b active per token
→ LongCat-2.5
That is its strongest area.
An enterprise with regional data-residency rules
→ Claude Opus 4.6 or LongCat-2.5
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
Claude Opus 4.6: where it fits
Anthropic's February 2026 flagship Opus and the first Opus-class model with a 1M-token context window, built for agentic coding and long-running professional tasks. Released February 5, 2026 by Anthropic, it is built for agentic coding and debugging in large codebases, long-running, multi-step autonomous agent tasks, frontier multidisciplinary reasoning (leads Humanity's Last Exam), and economically valuable knowledge work in finance and legal (GDPval-AA).
Its trade-offs are real: superseded by newer Claude Opus 4.7 and 4.8 (now a legacy model), and top-tier per-token price, and its 1M-token context shipped as beta. At $5 in / $25 out per million tokens, it sits in the premium price band.
LongCat-2.5: where it fits
Meituan's November 2, 2026 natively multimodal successor to LongCat-2.0 - 1.6T parameters and 1M context at $0.30/$1.20, with open weights planned but undated. Released November 2, 2026 by Meituan, it is built for native multimodal upgrade to LongCat-2.0 - 1.6T total parameters, about 48B active per token, limited-time API price of $0.30/$1.20 per million tokens (cached input $0.006), meituan-reported Terminal-Bench v2.1 of 88.4, up from 70.8 for LongCat-2.0, and openAI- and Anthropic-compatible API endpoints with a 1M-token context window.
Its trade-offs: aPI-only for now - GitHub and Hugging Face releases are planned but undated, and the license is unconfirmed (LongCat-2.0 is MIT), the $0.30/$1.20 rate is labeled limited-time, and Meituan says prices are subject to change, and benchmarks are Meituan's own, and sources found no independent score at launch. At $0.3 in / $1.2 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Claude Opus 4.6 (US) and LongCat-2.5 (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. LongCat-2.5 is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Claude Opus 4.6 and LongCat-2.5 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is Claude Opus 4.6 or LongCat-2.5 better for coding?
Public SWE-Bench figures are not available for LongCat-2.5, so the honest test is your own repository — run an identical real bug through both. By design, Claude Opus 4.6 leans toward agentic coding and debugging in large codebases while LongCat-2.5 leans toward native multimodal upgrade to longcat-2.0 - 1.6t total parameters, about 48b active per token, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Opus 4.6 or LongCat-2.5?
LongCat-2.5 is cheaper — $5/$25 per 1M tokens vs $0.3/$1.2 per 1M tokens, roughly 17× apart on input.
Which has the bigger context window?
Both advertise 1M (~1,500 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Opus 4.6 and LongCat-2.5 together?
Yes — a multi-model platform like LumiChats gives you Claude Opus 4.6, LongCat-2.5 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Opus 4.6 or LongCat-2.5?
LongCat-2.5 — released November 2, 2026, about 9 months after Claude Opus 4.6.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.