SQLCoder 7B needs ~8.9 GB VRAM. MacBook Air M2 16GB has 11.5 GB. With Q4_K_M quantization, expect ~15 tok/s.
Operating mode
Interactive favors responsiveness, while light API and scale-out lean harder on serving readiness. The fit stays the same, but the recommendation lens changes.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
Select quantization to explore
Fit status
Runs well
Decode
16.4 tok/s
TTFT
11831 ms
Safe context
8K
Memory
8.9 GB / 11.5 GB
This setup is broadly balanced for this model.
Shared-memory contention still exists
The OS, browser, and inference runtime all compete for the same physical memory pool, so real-world headroom is less forgiving than raw capacity suggests.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Runs well | 15.2 tok/s | 6937 ms | 8K |
| Coding | A | Runs well | 15.2 tok/s | 12718 ms | 8K |
| Agentic Coding | A | Tight fit | 15.2 tok/s | 18499 ms | 8K |
| Reasoning | A | Runs well | 15.2 tok/s | 15030 ms | 8K |
| RAG | A | Tight fit | 15.2 tok/s | 23124 ms | 8K |
How SQLCoder 7B (7B params) fits at each quantization level on MacBook Air M2 16GB (11.5 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | A79 |
Q3_K_S | 3 | 3.4 GB | Low | A80 |
NVFP4 | 4 |
Copy-paste commands to run SQLCoder 7B on your machine.
Run
ollama run sqlcoderYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
| 9B | S | 12.7 tok/s | ||
| 14B | A | 6.4 tok/s |
Yes, MacBook Air M2 16GB can run SQLCoder 7B with a A grade (Runs well). Expected decode speed: 15.2 tok/s.
SQLCoder 7B (7B parameters) requires approximately 8.9 GB of memory with Q4_K_M quantization.
The recommended quantization for SQLCoder 7B is Q4_K_M, which balances quality and memory efficiency.
On MacBook Air M2 16GB, SQLCoder 7B achieves approximately 15.2 tokens per second decode speed with a time-to-first-token of 12718ms using Q4_K_M quantization.
For coding workloads, SQLCoder 7B on MacBook Air M2 16GB receives a A grade with 15.2 tok/s and 8K context.
On MacBook Air M2 16GB, SQLCoder 7B can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/sqlcoder-7b-on-m2-air-16gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview:
3.9 GB |
| Medium |
| A81 |
Q4_K_M | 4 | 4.3 GB | Medium | A81 |
Q5_K_M | 5 | 5.0 GB | High | A82 |
Q6_K | 6 | 5.7 GB | High | A82 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | A81 |
F16 | 16 | 14.3 GB | Maximum | F0 |
| 8B | S | 14.3 tok/s |
| 8B | A | 14.3 tok/s |
| 14B | B | 6.4 tok/s |
Not always. MacBook Air M2 16GB can often fit larger models thanks to unified memory, but a discrete GPU with dedicated high-bandwidth VRAM may still decode faster once the model fits. For this combination, the important distinction is capacity versus sustained throughput.