text model comparison
Kimi K3 vs LongCat-2.5
Kimi K3 and LongCat-2.5 are both current text models, from Moonshot Kimi and Meituan. LongCat-2.5 is 90% cheaper per 1M input tokens than Kimi K3, $0.30 vs $3. In Meituan's LongCat-2.5 model card, Kimi K3 scores 88.3% on Terminal-Bench 2.1 and LongCat-2.5 88.4%. Both accept 1,048,576 tokens of context.
- Lower price per 1M input tokens
- LongCat-2.5$0.30 against $3
- Newer release
- LongCat-2.5Nov 2026 against Jul 2026
Data verified November 10, 2026 · Dataset 2026-11-10
Side by side
Kimi K3 and LongCat-2.5, line by line
Prices in effect today, compared at the same tier wherever both list one. The better value in each row is highlighted.
| Fact | Kimi K3 | LongCat-2.5 |
|---|---|---|
| Price | ||
| Price per 1M input tokens | $3 | $0.30 (better) |
| Price per 1M output tokens | $15 | $1.20 (better) |
| Independent benchmarks | ||
| Arena Text | 1487 Elo (#10 of 53) | Not measured |
| Arena WebDev | 1657 Elo (#14 of 48) | Not measured |
| GPQA Diamond | 93.1% (#19 of 43) | Not measured |
| FrontierMath Tiers 1-3 (v2) | 72.2% (#24 of 43) | Not measured |
| SimpleQA Verified | 50.6% (#22 of 40) | Not measured |
| Specs | ||
| Provider | Moonshot Kimi | Meituan |
| Release date | July 16, 2026 | November 2, 2026 |
| Access | API and open weights | API and open weights |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Max output | Not reported | 262,144 tokens |
| Input | text, image | text, image, video |
| Output | text | text |
No independent benchmark has scored both models yet. Each rank counts the current models scored on that benchmark.
Provider results
What the labs report
Results tables a lab published with one of its models, where it lists both Kimi K3 and LongCat-2.5. These are the lab's own figures, not independent measurements, and each table is read on its own: labs run benchmarks with different harnesses and budgets.
Meituan, LongCat-2.5 model card, November 4, 2026Meituan · 2026-11-10
| Benchmark | Kimi K3 | LongCat-2.5 |
|---|---|---|
| Terminal-Bench 2.1 | 88.3% | 88.4% (better) |
| Terminal-Bench 4.0 | 12.6% | 38.5% (better) |
| ProgramBenchalmost resolved | 17.5% | 25.5% (better) |
| DeepSWE v1.1 | 67.5% (better) | 64.6% |
| PaperBench | 77.5% | 82.1% (better) |
| SWE AtlasCodebase QnA | 54.3% | 58.3% (better) |
| SWE AtlasRefactoring | 49.5% | 55.2% (better) |
| SWE AtlasTest Writing | 42.2% | 47.8% (better) |
| NL2Repo | 58.0% | 60.5% (better) |
| BrowseComp | 91.2% | 91.9% (better) |
| AutomationBench v1.0.6 | 46.7% | 51.8% (better) |
| Humanity's Last Examwith tools, text-only | 56.0% | 63.1% (better) |
| Agents' Last Exam v1.1 | 35.2% | 38.5% (better) |
| ResearchRubrics | 78.8% | 81.0% (better) |
| MCP Atlas | 84.2% (better) | 83.1% |
| FrontierScience | 70.0% | 77.0% (better) |
| SpreadsheetBench 2 | 34.8% | 34.9% (better) |
| FinSearchCompT3 | 64.0% (better) | 63.4% |
| 3DCodeBenchtext to 3D | 49.3% | 55.4% (better) |
| Vision2Web | 79.0% (better) | 78.6% |
| CharXiv (RQ)with tools | 91.3% (better) | 90.2% |
| MathVisionwith tools | 97.8% (better) | 96.5% |
| VideoMME | 90.0% (better) | 85.2% |
Meituan's table from the LongCat-2.5 model card, with thinking on. Scores Meituan cites from public reports and scores it measured itself, which it calls indicative only, are both shown. DeepSeek-V4.1-Flash is the 1017 build. Left out here: the LongCat-2.0 column (not in this catalogue), Meituan's own evaluations (LongCat AppDev, LongCatClawBench), Artificial Analysis's GDPval-AA, and JobBench, PosterBench and Claw-Eval, which we could not confirm are public.
Charts
Against every current text model
Where Kimi K3 and LongCat-2.5 land among the current models of their task, on every independent benchmark, on price and on context.
Where each stands
Only Kimi K3 has a current Arena Text score: #10 of 53. Each bar is the share of current models it beats.
Independent benchmarks
Arena Text
Kimi K3:#10of 53
1,487 Elo · ahead of 81%
LongCat-2.5: Not scored
Arena WebDev
Kimi K3:#14of 48
1,657 Elo · ahead of 72%
LongCat-2.5: Not scored
GPQA Diamond
Kimi K3:#19of 43
93.1% · ahead of 57%
LongCat-2.5: Not scored
FrontierMath Tiers 1-3 (v2)
Kimi K3:#24of 43
72.2% · ahead of 45%
LongCat-2.5: Not scored
SimpleQA Verified
Kimi K3:#22of 40
50.6% · ahead of 46%
LongCat-2.5: Not scored
Price and context
Price per 1M input tokens
Kimi K3:#46of 61
$3 · cheaper than 25%
LongCat-2.5:#12of 61
$0.30 · cheaper than 75%
Price per 1M output tokens
Kimi K3:#45of 61
$15 · cheaper than 25%
LongCat-2.5:#12of 61
$1.20 · cheaper than 77%
Context window
Kimi K3:#12of 70
1.05M tokens · longer than 67%
LongCat-2.5:#12of 70
1.05M tokens · longer than 67%
Quality against price
Kimi K3 scores 1,487 at $6 (blended price per 1M tokens). The line joins the current models no other beats on both price and Arena Text score; hover any point to name it.
Quality against price: the data
| Model | Provider | Blended price per 1M tokens | Arena Text (Elo) |
|---|---|---|---|
| Gemini 4 Carbon | $4 | 1,526 | |
| Gemini 4 Argon | $4 | 1,522 | |
| Muse Wonder | Meta | $8 | 1,511 |
| Claude Opus 5.5 | Anthropic | $8 | 1,506 |
| Claude Fable 5 | Anthropic | $20 | 1,504 |
| Claude Fable 5.1 | Anthropic | $20 | 1,503 |
| Gemini 3.8 Flash | $1.50 | 1,497 | |
| Muse Spark 1.3 | Meta | $2 | 1,496 |
| Claude Opus 5 | Anthropic | $10 | 1,490 |
| Kimi K3 | Moonshot Kimi | $6 | 1,487 |
| GPT-5.6 Sol | OpenAI | $8 | 1,485 |
| Qwen3.8-Max | Alibaba Qwen | $3 | 1,484 |
| Gemini 3.6 Flash | $3 | 1,483 | |
| GLM-5.3 | Z.ai | $2.15 | 1,483 |
| Claude Opus 4.8 | Anthropic | $10 | 1,482 |
| GPT-6.1 Sol | OpenAI | $4 | 1,482 |
| GPT-5.5 | OpenAI | $11 | 1,481 |
| MiMo-V2.6-Pro | Xiaomi MiMo | $0.54 | 1,480 |
| GPT-5.4 | OpenAI | $5.63 | 1,475 |
| DeepSeek-V4.1-Flash | DeepSeek | $0.52 | 1,475 |
| GPT-6 Astra | OpenAI | $20 | 1,474 |
| GLM-5.3-Flash | Z.ai | $0.24 | 1,474 |
| Gemini 3 Flash Preview | $1.13 | 1,473 | |
| Grok 4.20 | xAI | $1.56 | 1,472 |
| Claude Sonnet 5.5 | Anthropic | $4 | 1,472 |
| GPT-5.6 Terra | OpenAI | $4.50 | 1,468 |
| Grok 4.5 | xAI | $3 | 1,466 |
| DeepSeek-V4-Pro | DeepSeek | $1.98 | 1,464 |
| Claude Sonnet 5 | Anthropic | $4 | 1,461 |
| GPT-6 Sol | OpenAI | $4 | 1,457 |
| Grok 4.6 | xAI | $3 | 1,456 |
| Gemini 3.5 Flash-Lite | $0.85 | 1,455 | |
| GPT-5.6 Luna | OpenAI | $0.45 | 1,453 |
| MiMo-V2.6-Flash | Xiaomi MiMo | $0.18 | 1,448 |
| Step 5 Preview | StepFun | $1.43 | 1,448 |
| Grok 4.3 | xAI | $1.56 | 1,442 |
| Grok 4.7 | xAI | $3 | 1,442 |
| GPT-6 Luna | OpenAI | $0.20 | 1,441 |
| Mistral Large 4 | Mistral AI | $1.05 | 1,423 |
| Claude Haiku 5.5 | Anthropic | $0.20 | 1,422 |
| GPT-4.1 | OpenAI | $3.50 | 1,415 |
| Inkling 2 Small | Thinking Machines Lab | $0.47 | 1,412 |
| Solar Pro 4 | Upstage | $0.52 | 1,387 |
| GPT-4.1 mini | OpenAI | $0.70 | 1,383 |
| GPT-4.1 nano | OpenAI | $0.18 | 1,322 |
Cost
What each costs
Example workloads at each provider's listed rates, then every other rate either one lists. The cheaper figure in each row is highlighted.
The same work, priced
For 10M input and 2M output tokens, Kimi K3 costs 11 times as much as LongCat-2.5, at each provider's listed rates.
10M input and 2M output tokens
Kimi K3 costs 11× as much
- Kimi K3
- $60
- LongCat-2.5
- $5.40
The same, with 9M of the input tokens cached
Kimi K3 costs 13× as much
- Kimi K3
- $35.70
- LongCat-2.5
- $2.75
| Workload or rate | Kimi K3 | LongCat-2.5 |
|---|---|---|
| Example workloads | ||
| 10M input and 2M output tokens | $60 | $5.40 (better) |
| The same, with 9M of the input tokens cached | $35.70 | $2.75 (better) |
| Other listed rates | ||
| 1M input tokens, cached | $0.30 | $0.006 (better) |
Your own bill will differ. These figures use list prices and example workloads. The AI Model Cost Audit reviews your real usage, shortlists models that score as well for each task for less, and estimates the savings.
Launch price $100, regular price $150
Verdict
When to choose each
Kimi K3
Where it leads
No measured lead over LongCat-2.5 in this data.
Best for
- Teams that want a frontier-scale model they can also self-host, with one architecture across both paths
- Long-context work at mid-tier hosted pricing
Watch out for
- Hosted rates match Claude Sonnet 5 exactly at $3 / $15 while offering a larger context window, so the comparison turns on capability rather than price
- Running the open weights shifts cost to infrastructure, which the token rates recorded here do not represent
- Moonshot’s self-reported results place it ahead of Claude Opus 4.8 and GPT-5.5 but behind Claude Fable 5 and GPT-5.6 Sol; none of this was reproduced independently here
LongCat-2.5
Where it leads
- Lower input and output prices, $0.30 and $1.20 vs $3 and $15 per 1M tokens
- Accepts video input
- Cheaper cached input, $0.006 vs $0.30 per 1M tokens
Best for
- Coding agents working through whole projects in Claude Code, Codex or similar harnesses, on the API or self-hosted
- Visual coding and design work that mixes screenshots or screen recordings with code
Watch out for
- The recorded rates are a limited-time discount: Meituan publishes no list price and no end date
- No independent benchmark has scored it yet, and Meituan calls the scores it measured in-house for its own table indicative only
From benchmark to production
Building on Kimi K3 or LongCat-2.5?
Public scores rarely hold on your own data. We test both models on your real tasks, then build the agent or pipeline around the one that wins.
AI Model Cost AuditLaunch price $100, regular price $150What the audit includes
FAQ
Kimi K3 vs LongCat-2.5 FAQ
Which is cheaper, Kimi K3 or LongCat-2.5?
LongCat-2.5 is 90% cheaper per 1M input tokens than Kimi K3, $0.30 vs $3. For 10M input and 2M output tokens, Kimi K3 costs $60 and LongCat-2.5 $5.40 at standard rates.
Which is cheaper with prompt caching, Kimi K3 or LongCat-2.5?
Kimi K3 charges $0.30 per 1M cached input tokens, 90% below its standard input rate, and LongCat-2.5 $0.006, 98% below. With 9M of 10M input tokens cached and 2M output tokens, Kimi K3 costs $35.70 and LongCat-2.5 $2.75.
How do Kimi K3 and LongCat-2.5 compare in Meituan's own results?
In the LongCat-2.5 model card (November 4, 2026), LongCat-2.5 leads on Terminal-Bench 2.1, 88.4% to 88.3%; LongCat-2.5 leads on Terminal-Bench 4.0, 38.5% to 12.6%; LongCat-2.5 leads on ProgramBench (almost resolved), 25.5% to 17.5%. These are Meituan's figures, not independent measurements.
Which has the larger context window, Kimi K3 or LongCat-2.5?
Both accept 1,048,576 tokens of context.
How do Kimi K3 and LongCat-2.5 differ in features?
Kimi K3 takes text and image input; LongCat-2.5 takes text, image and video.
Further reading
More on Kimi K3 and LongCat-2.5
Articles on Kimi K3 and LongCat-2.5
- LongCat-2.5 vs Claude Opus 5: Read the Benchmarks FirstNovember 4, 2026
- Qwen vs DeepSeek vs Kimi for Agents and CodingAugust 6, 2026
- Kimi K3 vs Opus 5 vs GPT-5.6 Sol: which model should you use?July 31, 2026
Related comparisons
- Claude Opus 5.5 vs Kimi K3
- Inkling 2 Small vs LongCat-2.5
- GPT-6 Luna vs Kimi K3
- Claude Opus 5.5 vs LongCat-2.5
- DeepSeek-V4.1-Flash vs Kimi K3
- Claude Opus 5 vs LongCat-2.5
- GPT-6 Astra vs Kimi K3
- DeepSeek-V4.1-Flash vs LongCat-2.5
- Gemini 3.8 Flash vs Kimi K3
- Gemini 3.1 Flash-Lite vs LongCat-2.5
- GLM-5.3 vs Kimi K3
- Gemini 3.5 Flash-Lite vs LongCat-2.5
Production evaluation
Choosing between Kimi K3 and LongCat-2.5?
Public benchmarks narrow the shortlist. We run both on your own tasks, data and cost limits, then build the routing and review controls to run the winner in production.
- A head-to-head evaluation on your real workload
- Routing between models by cost and difficulty