Phi 4 Open vs 
Mistral Large Paid
Phi 4 vs Mistral Large 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 — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$0.14 /M outputNo per-token fees if you self-host
$6 /M outputManaged API (no infra to run)
Phi 4 vs Mistral Large specs
| Spec | Phi 4 | Mistral Large | Winner |
|---|---|---|---|
| Maker | Microsoft | Mistral AI | – |
| Type | Open-weight | Proprietary | |
| Context window | 16K tokens | 128K tokens | |
| Input price | $0.07/M · free self-host | $2/M | |
| Output price | $0.14/M · free self-host | $6/M | |
| Vision / multimodal | No | No | – |
| Tool / function calling | No | Yes | |
| Self-hostable | Yes | No (API only) | |
| License | MIT | Proprietary |
Price gap & when to choose each
Phi 4 is ~43× cheaper than Mistral Large on output tokens ($0.14 vs $6 per M tokens).
- You want to self-host or run on your cloud
- You prioritize data privacy & control
- You want the lowest operating costs
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You need the longer 128K context window
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | Phi 4 | Mistral Large |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✗ | ✗ |
| Tool / function calling | ✗ | ✓ |
| 1M+ context window | ✗ | ✗ |
Benchmarks: Phi 4 vs Mistral Large
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Phi 4 and Mistral Large score
| Criterion | Phi 4 | Mistral Large |
|---|---|---|
| Cost-efficiency | 5.0 | 4.0 |
| Context window | 2.0 | 3.5 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 2.0 | 3.5 |
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
Phi 4 Open
[Microsoft Research](/microsoft) Phi-4 is designed to perform well in complex reasoning tasks and can operate efficiently in situations with limited memory or where quick responses are needed. At 14 billion...
Mistral Large Paid
This is Mistral AI's flagship model, Mistral Large 2 (version `mistral-large-2407`). It's a proprietary weights-available model and excels at reasoning, code, JSON, chat, and more. Read the launch announcement [here](https://mistral.ai/news
Frequently asked questions
Is Phi 4 as good as Mistral Large?
Phi 4 is open-weight and competitive on many tasks, but Mistral Large 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 Phi 4 locally?
Yes. Phi 4 has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Mistral Large is API-only and cannot be self-hosted.
How much cheaper is Phi 4?
Phi 4 costs $0.14/M output vs $6/M for Mistral Large — roughly 43x cheaper via API, and free if you self-host.
Phi 4 vs Mistral Large — which should I pick in 2026?
Choose Phi 4 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 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 →