Muse Glimmer 30B Open vs 
Codestral 2508 Paid
Muse Glimmer 30B vs Codestral 2508 compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.
Codestral 2508 — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$1.1 /M outputNo per-token fees if you self-host
$0.9 /M outputManaged API (no infra to run)
Muse Glimmer 30B vs Codestral 2508 specs
| Spec | Muse Glimmer 30B | Codestral 2508 | Winner |
|---|---|---|---|
| Maker | Meta | Mistral AI | – |
| Type | Open-weight | Proprietary | |
| Context window | 131K tokens | 256K tokens | |
| Input price | $0.3/M · free self-host | $0.3/M | = Tie |
| Output price | $1.1/M · free self-host | $0.9/M | |
| Vision / multimodal | Yes | No | |
| Tool / function calling | Yes | Yes | = Tie |
| Self-hostable | Yes | No (API only) | |
| License | Open weights | Proprietary |
Price gap & when to choose each
- You want to self-host or run on your cloud
- You prioritize data privacy & control
- You are building open or reproducible AI
- You want frontier performance through a managed API
- You need the longer 256K context window
- You want the lower output price
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | Muse Glimmer 30B | Codestral 2508 |
|---|---|---|
| Open weights (downloadable) | ✓ | ✗ |
| Self-hostable | ✓ | ✗ |
| Runs fully offline | ✓ | ✗ |
| Vision / multimodal | ✓ | ✗ |
| Tool / function calling | ✓ | ✓ |
| 1M+ context window | ✗ | ✗ |
Benchmarks: Muse Glimmer 30B vs Codestral 2508
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How Muse Glimmer 30B and Codestral 2508 score
| Criterion | Muse Glimmer 30B | Codestral 2508 |
|---|---|---|
| Cost-efficiency | 4.5 | 5.0 |
| Context window | 3.5 | 4.0 |
| Openness | 5.0 | 1.5 |
| Self-hosting | 5.0 | 1.0 |
| Multimodality | 5.0 | 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
Muse Glimmer 30B Open
Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon...
Codestral 2508 Paid
Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. [Blog Post](https://mistral.ai/ne
Other models in these families
These variants are tracked but not compared here — one page per family keeps the comparison readable.
Frequently asked questions
Is Muse Glimmer 30B as good as Codestral 2508?
Muse Glimmer 30B is open-weight and competitive on many tasks, but Codestral 2508 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 Muse Glimmer 30B locally?
Yes. Muse Glimmer 30B has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. Codestral 2508 is API-only and cannot be self-hosted.
Muse Glimmer 30B vs Codestral 2508 — which should I pick in 2026?
Choose Muse Glimmer 30B 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 Codestral 2508 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 →