🇪🇺 Europe (collective)💻 CodeReleased February 2024
StarCoder 2
BigCode
Open-sourceFreeSelf-hostRGPD
Verdict
A solid pick for self-hosting and full data control.
Overview
StarCoder 2 comes from the BigCode collective (HuggingFace + ServiceNow). Apache 2, fully transparent training data, ideal for absolute sovereignty or local/edge deployments. Performance trailing frontiers but it's the only fully transparent one.
Skill profile
Verified benchmarks
HumanEval46.3%
What do these scores mean?
HumanEval46.3%fair
Python code generation from specifications.
Strengths
- Has a free tier
- Open-source and self-hostable
Limitations
- Light safety filters
- API pricing not disclosed
Who is it for
A good fit if…
- you build with a coding agent
- you want to control cost or self-host
- you have GDPR constraints
Skip it if…
- you want strict guardrails
Ideal use cases
- Local autocompletion
- Code on edge
- Lightweight apps
- IDE plugins
Access & availability
Free tier availableSelf-hostable (open weights)
Key specifications
Context
16K
Input price
—
Output price
—
Speed
200 tok/s
Price not auditedBenchmarks not audited
Privacy
GDPR-compliantHosting : EU/selfAnonymizable data
Run it locally
Desktop with solid GPU / 32GB+ Mac11k674
| Quantization | Disk | RAM / VRAM | Typical hardware |
|---|---|---|---|
| Q4 · recommended | 9.1 GB | 12 GB | 32GB PC / 24GB Mac / RTX 4070 Ti+ |
| Q8 · balanced | 17.1 GB | 21 GB | 32GB Mac / RTX 3090-4090 |
| FP16 · max quality | 32 GB | 37 GB | 64GB Mac / dual 24GB GPUs |
Estimates for a moderate context. Long contexts need more RAM (KV cache).
🤗 Hugging Face
ollama run starcoder2:15b
Advanced data · for expertsArchitecture, modalities, detailed cost, full benchmarks▾
Advanced data · for experts
Architecture, modalities, detailed cost, full benchmarks
Architecture
Dense
Size
15B
Cutoff date
Aug 2023
Inputs
text
Outputs
code
License
apache-2
Hosting
EU/self
Hallucination score
2/5
Estimated cost (API)
Typical exchange (~3k in / 1k out)
Not disclosed
1M in + 1M out
Not disclosed
All benchmarks
| Arena Elo | — |
| MMLU | — |
| GPQA | — |
| HumanEval | 46.3% |
| SWE-Bench | — |
| MATH | — |