StarCoder2 7B vs CodeGemma 7B
Side-by-side comparison of hardware requirements, quantization options, and specifications to help you choose the right model for your device.
Specifications Comparison
| Spec | StarCoder2 7B | CodeGemma 7B |
|---|---|---|
| Parameters | 7B | 8.5B |
| Architecture | starcoder | gemma |
| License | bigcode-openrail-m | Gemma |
| Context Length | 16K tokens | 8K tokens |
| Category | Code Model | Code Model |
| Author | BigCode | |
| HF Downloads | 10.1K | 7.4K |
| VRAM Range | 4.66 - 7.61 GB | 5.46 - 8.95 GB |
| Quantizations | 2 options | 2 options |
| Best Quality Score | 98% | 98% |
Quantization Options
StarCoder2 7B
CodeGemma 7B
In-depth comparison
For the typical user, StarCoder2 7B is the better choice due to its lower VRAM requirement and larger context window, which allows for more extensive code generation without requiring high-end hardware.
When to choose StarCoder2 7B
StarCoder2 7B is the better pick for users who need to handle longer code contexts up to 16,384 tokens, which is ideal for generating and understanding large codebases or complex functions. Its lower VRAM requirement of 4.7GB makes it more accessible for users with mid-range GPUs, and it still delivers high-quality code completions and bug fixes, making it a versatile choice for both professional and hobbyist developers.
When to choose CodeGemma 7B
CodeGemma 7B is the better pick for users who prioritize slightly higher parameter count and a strong focus on instruction-tuned code generation. With 8.5 billion parameters, it may offer more nuanced and contextually relevant outputs, especially in scenarios where the code needs to follow specific instructions or guidelines. However, it requires more VRAM (5.5GB) and has a smaller context window (8,192 tokens), which might limit its usability on less powerful hardware.
Quality
Both models have a best quality score of 98%, indicating they perform similarly in terms of output quality. However, CodeGemma 7B's slightly higher parameter count (8.5B vs. 7B) suggests it might generate more nuanced and contextually relevant code, especially when following specific instructions. StarCoder2 7B, on the other hand, benefits from a larger context window, which can be crucial for understanding and generating more complex code structures.
Performance & hardware fit
StarCoder2 7B has a lower minimum VRAM requirement of 4.7GB compared to CodeGemma 7B's 5.5GB, making it more suitable for users with mid-range GPUs. This lower VRAM requirement also means it can run more efficiently on a wider range of hardware, potentially offering faster inference times. However, CodeGemma 7B's slightly higher parameter count might result in marginally slower performance but could provide more detailed and accurate outputs.
Use-case fit
| coding | StarCoder2 7B | StarCoder2 7B's larger context window and lower VRAM requirement make it more practical for handling large codebases and running on a variety of hardware setups. |
| creative writing | Tie | Both models are primarily designed for code generation, so neither has a clear advantage in creative writing tasks. |
| RAG / retrieval | StarCoder2 7B | StarCoder2 7B's larger context window (16,384 tokens) makes it better suited for retrieval-augmented generation tasks that require processing long documents or code snippets. |
| agent / tool use | CodeGemma 7B | CodeGemma 7B's instruction-tuned nature and slightly higher parameter count make it more adept at following specific instructions, which is beneficial for agent or tool use scenarios. |
| running on consumer GPU (8-12GB) | StarCoder2 7B | StarCoder2 7B's lower VRAM requirement of 4.7GB makes it more compatible with consumer GPUs in the 8-12GB range. |
| long context (16K+) | StarCoder2 7B | StarCoder2 7B supports a context window of 16,384 tokens, making it the clear winner for long-context tasks. |
StarCoder2 7B wins for most users due to its lower VRAM requirement and larger context window, making it more accessible and versatile. CodeGemma 7B is the better choice for users who need more nuanced instruction-tuned code generation and have the hardware to support its higher VRAM requirements.