MELongCat 2.0 Open vs 
Mistral Large 3 2512 (batch) Paid
LongCat 2.0 vs Mistral Large 3 2512 (batch) compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Mistral Large 3 2512 (batch) — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$1.2 /M outputNo per-token fees if you self-host
$0.75 /M outputManaged API (no infra to run)
LongCat 2.0 vs Mistral Large 3 2512 (batch) specs
| Spec | LongCat 2.0 | Mistral Large 3 2512 (batch) | Winner |
|---|---|---|---|
| Maker | Meituan | Mistral AI | – |
| Type | Open-weight | Proprietary | MELongCat 2.0 |
| Context window | 1M tokens | 262K tokens | MELongCat 2.0 |
| Input price | $0.3/M · free self-host | $0.25/M | |
| Output price | $1.2/M · free self-host | $0.75/M | |
| Vision / multimodal | No | Yes | |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | MELongCat 2.0 |
| License | Open weights | Proprietary | MELongCat 2.0 |
Price gap & when to choose each
Mistral Large 3 2512 (batch) is ~1.6× cheaper than LongCat 2.0 on output tokens ($0.75 vs $1.2 per M tokens).
- You want to self-host or run on your cloud
- You need the longer 1M context window
- You prioritize data privacy & control
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You want the lower output price
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | LongCat 2.0 | Mistral Large 3 2512 (batch) |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✗ | ✓ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✓ | ✗ |
Benchmarks: LongCat 2.0 vs Mistral Large 3 2512 (batch)
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How LongCat 2.0 and Mistral Large 3 2512 (batch) score
| Criterion | LongCat 2.0 | Mistral Large 3 2512 (batch) |
|---|---|---|
| Cost-efficiency | 4.5 | 5.0 |
| Context window | 5.0 | 4.0 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 3.5 | 5.0 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
What each model is
LongCat 2.0 Open
LongCat 2.0 is a sparse mixture-of-experts language model from Meituan, with 48B active parameters out of 1.6T total. It is suited for coding, repository-level changes, long-horizon problem solving, and agentic...
Mistral Large 3 2512 (batch) Paid
Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.
Frequently asked questions
Is LongCat 2.0 as good as Mistral Large 3 2512 (batch)?
LongCat 2.0 is open-weight and competitive on many tasks, but Mistral Large 3 2512 (batch) may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.
Can I run LongCat 2.0 locally?
Yes. LongCat 2.0 has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Mistral Large 3 2512 (batch) is API-only and cannot be self-hosted.
LongCat 2.0 vs Mistral Large 3 2512 (batch) — which should I pick in 2026?
Choose LongCat 2.0 if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose Mistral Large 3 2512 (batch) if you want frontier capability through a managed API with zero infrastructure to run.
People also compare
Explore more open-source AI
Browse the full open-source model leaderboard, thousands of tools and live benchmarks — all in one place.
Open the leaderboard →