GPT-5.1 vs LongCat-2.5
OpenAI · US | Meituan · China · Updated June 2026
Quick verdict
Pick GPT-5.1 for adaptive reasoning that scales compute to task difficulty or general-purpose reasoning, coding and tool use. 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.
GPT-5.1 (OpenAI, 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. GPT-5.1 is openAI's late-2025 GPT-5.1 at $1.25/$10 — a capable general model since surpassed by the GPT-5.2–5.6 line. 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. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: LongCat-2.5 is about 4.2× cheaper on input ($0.3/$1.2 per 1M tokens vs $1.25/$10 per 1M tokens) — meaningful once you are processing millions of tokens a month.
- ▸Context window: LongCat-2.5 holds 2.5× more — 1M tokens (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: LongCat-2.5 is the newer model by about 12 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 | GPT-5.1 | LongCat-2.5 |
|---|---|---|
| Provider | OpenAI (US) | Meituan (China) |
| Released | November 13, 2025 | November 2, 2026 |
| Context window | 400K (~600 pages) | 1M tokens (~1,500 pages) |
| Price (in/out) | $1.25/$10 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 | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Adaptive reasoning that scales compute to task difficulty
GPT-5.1
GPT-5.1 lists adaptive reasoning that scales compute to task difficulty among its strengths; LongCat-2.5 does not.
General-purpose reasoning, coding and tool use
GPT-5.1
GPT-5.1 lists general-purpose reasoning, coding and tool use among its strengths; LongCat-2.5 does not.
A large ~400K context for long documents and sessions
GPT-5.1
GPT-5.1 lists a large ~400K context for long documents and sessions 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
Its 1M tokens window holds about 2.5× more than GPT-5.1's 400K in a single prompt.
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 GPT-5.1 ($1.25/$10 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
GPT-5.1 is comparatively weak here — no reliably published SWE-Bench Verified figure
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.
Largest single-prompt input
LongCat-2.5
Its 1M tokens window is about 2.5× larger than GPT-5.1's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ LongCat-2.5
At $0.3/$1.2 per 1M tokens it undercuts GPT-5.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ LongCat-2.5
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is adaptive reasoning that scales compute to task difficulty
→ GPT-5.1
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
→ GPT-5.1 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.
GPT-5.1: where it fits
OpenAI's late-2025 GPT-5.1 at $1.25/$10 — a capable general model since surpassed by the GPT-5.2–5.6 line. Released November 13, 2025 by OpenAI, it is built for adaptive reasoning that scales compute to task difficulty, general-purpose reasoning, coding and tool use, a large ~400K context for long documents and sessions, and text and image input.
Its trade-offs are real: superseded by GPT-5.2 through GPT-5.6 — kept for compatibility rather than being current, no reliably published SWE-Bench Verified figure, exact context window unconfirmed (400K vs 410K across trackers), and premium output price at $10/1M for a now-older model. At $1.25 in / $10 out per million tokens, it sits in the mid 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." GPT-5.1 (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 GPT-5.1 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 GPT-5.1 or LongCat-2.5 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, GPT-5.1 leans toward adaptive reasoning that scales compute to task difficulty 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, GPT-5.1 or LongCat-2.5?
LongCat-2.5 is cheaper — $1.25/$10 per 1M tokens vs $0.3/$1.2 per 1M tokens, roughly 4.2× apart on input.
Which has the bigger context window?
LongCat-2.5 — 1M tokens vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.1 and LongCat-2.5 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.1, 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, GPT-5.1 or LongCat-2.5?
LongCat-2.5 — released November 2, 2026, about 12 months after GPT-5.1.
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.