LongCat-2.0 vs GPT-5.5
Compare API pricing and public benchmark scores for both models.
API Pricing (USD per 1M tokens)
| Model | Input | Output | Output vs LongCat (standard) |
|---|---|---|---|
| LongCat-2.0 (standard) | $0.75 | $2.95 | — |
| LongCat-2.0 (promo) | $0.30 | $1.20 | — |
| GPT-5.5 | $5.00 | $30.00 | ~10× more expensive (output) |
On output tokens — which dominate agentic coding loops — LongCat-2.0 at standard pricing costs roughly one-tenth of GPT-5.5. At promo pricing ($1.20/M output), the gap widens to roughly 25×. Input-side, LongCat is about 6–7× cheaper than GPT-5.5 at standard rates.
LongCat also offers free cached-context reads on cache hits, which further lowers effective cost for agents that resend large system prompts or codebase snapshots every turn.
Pricing from public API listings; verify current rates before budgeting. See our full pricing comparison.
Benchmarks: Where Each Model Wins
| Benchmark | LongCat-2.0 | GPT-5.5 | Takeaway |
|---|---|---|---|
| SWE-bench Pro | 59.5 | 58.6 | LongCat slightly ahead (+0.9) |
| FORTE (productivity / workflow) | 73.2 | 77.8 | GPT-5.5 clearly ahead (+4.6) |
| Terminal-Bench 2.1 | 70.8 | — | LongCat-reported; no public GPT-5.5 figure here |
How to read SWE-bench Pro (+0.9)
A single-point gap at this scale is often within benchmark variance. Both models score strongly on deep software engineering tasks.
How to read FORTE (73.2 vs 77.8)
FORTE simulates broader productivity and general workflow scenarios — not pure code patching. Here GPT-5.5 leads by 4.6 points while LongCat ties Claude Opus 4.6 at 73.2. That pattern suggests LongCat-2.0's relative strength is programming and agentic coding, not general office-style workflow simulation. If your pipeline is mostly "edit this codebase" or "run these terminal tools," SWE-bench Pro is the closer signal. If you need open-ended multi-app productivity agents, GPT-5.5 still has the edge on reported numbers.
Practical Decision Guide
- Choose LongCat-2.0 when token volume is high, output cost dominates, and tasks are coding- or terminal-heavy
- Choose GPT-5.5 when FORTE-style general workflow quality matters more than per-token economics
- Run both on a sample if SWE-bench Pro is close — your stack, language mix, and test harness may differ from public reports