Sqlcoder 7B 2 — Hardware Requirements & GPU Compatibility
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SQLCoder 7B 2 is a 6.7-billion-parameter model from Defog, purpose-built for converting natural-language questions into SQL queries. Fine-tuned specifically on text-to-SQL tasks, it consistently outperforms much larger general-purpose models when the job is generating accurate, executable SQL against real database schemas. For developers and data analysts who regularly query databases, running SQLCoder locally means fast, private SQL generation without sending proprietary schema details to an external API. It works best when provided with table definitions as context and is particularly strong on PostgreSQL, MySQL, and SQLite dialects.
24.1K downloads
436 likesSpecifications
- Publisher
- defog
- Parameters
- 6.7B
- Architecture
- LlamaForCausalLM
- Context Length
- 16,384 tokens
- Vocabulary Size
- 32,016
- Release Date
- 2024-02-05
- License
- CC BY-SA 4.0
Get Started
HuggingFace
How Much VRAM Does Sqlcoder 7B 2 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 4.2 GB | 11.8 GB | 2.86 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 4.3 GB | 11.8 GB | 2.95 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 4.7 GB | 12.2 GB | 3.29 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 4.7 GB | 12.3 GB | 3.37 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 5.4 GB | 12.9 GB | 4.04 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 6.2 GB | 13.7 GB | 4.80 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 6.9 GB | 14.4 GB | 5.56 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 8.1 GB | 15.6 GB | 6.74 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run Sqlcoder 7B 2?
Q4_K_M · 5.4 GBSqlcoder 7B 2 (Q4_K_M) requires 5.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 8+ GB is recommended. Using the full 16K context window can add up to 7.5 GB, bringing total usage to 12.9 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Sqlcoder 7B 2?
Q4_K_M · 5.4 GB58 devices with unified memory can run Sqlcoder 7B 2, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomWhere to Download Sqlcoder 7B 2
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does Sqlcoder 7B 2 need?
Sqlcoder 7B 2 requires 5.4 GB of VRAM at Q4_K_M, or 14.8 GB at FP16. Full 16K context adds up to 7.5 GB (12.9 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 6.7B × 4.8 bits ÷ 8 = 4 GB
KV Cache + Overhead ≈ 1.4 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 8.9 GB (at full 16K context)
VRAM usage by quantization
Q4_K_M5.4 GBQ4_K_M + full context12.9 GB- What's the best quantization for Sqlcoder 7B 2?
For Sqlcoder 7B 2, Q4_K_M (5.4 GB) offers the best balance of quality and VRAM usage. Q5_0 (5.6 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 4.2 GB.
VRAM requirement by quantization
Q2_K4.2 GBQ3_K_L4.8 GBQ4_K_M ★5.4 GBQ5_05.6 GBQ5_K_M6.2 GBFP1614.8 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Sqlcoder 7B 2 on a Mac?
Sqlcoder 7B 2 requires at least 4.2 GB at Q2_K, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Sqlcoder 7B 2 locally?
Yes — Sqlcoder 7B 2 can run locally on consumer hardware. At Q4_K_M quantization it needs 5.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Sqlcoder 7B 2?
At Q4_K_M, Sqlcoder 7B 2 can reach ~812 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~121 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 5.4 × 0.65 = ~959 tok/s
Estimated speed at Q4_K_M (5.4 GB)
~959 tok/s~121 tok/s~959 tok/s~812 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Sqlcoder 7B 2?
At Q4_K_M, the download is about 4.04 GB. The full-precision FP16 version is 13.48 GB. The smallest option (Q2_K) is 2.86 GB.
- Which GPUs can run Sqlcoder 7B 2?
50 consumer GPUs can run Sqlcoder 7B 2 at Q4_K_M (5.4 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 39 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Sqlcoder 7B 2?
59 devices with unified memory can run Sqlcoder 7B 2 at Q4_K_M (5.4 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.