Last refreshed 2026-05-01. Next refresh: weekly.
Why use StarCoder2 15B on NVIDIA NIM?
NVIDIA NIM offers StarCoder2 15B with competitive pricing. NVIDIA NIM is NVIDIA's deployment platform for GPU-accelerated inference microservices.
Compare StarCoder2 15B across 3 providers to find the best fit for your use caseSetup recipe
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starcoder2-15b.Gotchas
No curated gotchas have been sourced for this exact provider/model route yet.
Compare StarCoder2 15B Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Fireworks AI | $0.20 | $0.20 |
| DeepInfra | $0.20 | $0.60 |
| NVIDIA NIM | — | — |
Pricing
| Type | Rate |
|---|---|
| GPU Hour Rate | $1.00/GPU·hr |
Capabilities
About StarCoder2 15B
StarCoder2-15B is a sophisticated large language model, expertly crafted for code generation and understanding. Developed by the BigCode project, it features 15 billion parameters and is trained on The Stack v2, a vast dataset of over 4 trillion tokens from more than 600 programming languages. Its advanced transformer decoder architecture, equipped with a grouped-query and sliding window attention mechanism and a Fill-in-the-Middle training objective, allows a context window of 16,384 tokens. In addition to generating and completing code, the model excels in tasks like code summarization and retrieving relevant snippets through natural language queries. The training leveraged NVIDIA's NeMo framework and the Eos Supercomputer, while usage is governed by the BigCode Open RAIL-M license, supporting royalty-free and commercial use.
FAQ
What is the context window for StarCoder2 15B on NVIDIA NIM?
StarCoder2 15B supports a 8,000 token context window on NVIDIA NIM.
How does NVIDIA NIM compare to other StarCoder2 15B providers?
StarCoder2 15B is available from 3 providers. The cheapest input pricing is $0.20/1M tokens from Fireworks AI.
Who created StarCoder2 15B?
StarCoder2 15B was created by ServiceNow Research as part of the StarCoder 2 model family.
Is StarCoder2 15B open source?
StarCoder2 15B is open source according to the seed data.