MODEL ARCHITECTURE SPEC • ALIBABA CLOUD7.6B Dense
Qwen 2.5 Coder 7B Instruct VRAM & inference speed
7.6B Total ParamsDense Architecture28 Layers • 4 KV Heads32K Default Ctx (Max 128K)Ollama: qwen2.5-coder:7b
Accurate memory requirements, KV cache footprint, and tokens/sec generation benchmarks for running Qwen 2.5 Coder 7B Instruct across local GPUs, Apple Silicon Macs, and cloud instances.
✓ FITS IN VRAM6.41 GB (53%)~49 t/s
Qwen 2.5 Coder 7B Instruct on NVIDIA GeForce RTX 3060 (12GB)
✓ Fits Comfortably in VRAM
✓ FITS IN VRAM
Required VRAM
6.41 GB
53% of hardware capacity (12 GB)Est. Decode Speed
~49 tok/s
Dense model @ 360 GB/sAvailable Headroom
+5.59 GB
Safe for OS display & full contextMemory Allocation & Headroom
6.41 GB allocated of 12 GB capacity
53% utilized
Weights: 4.56 GB
KV: (32K): 0.94 GB
Overhead: 0.91 GB
Free Headroom: +5.59 GB
Architecture & Throughput Transparency: Single-user decode speed (~49 tok/s) is memory-bandwidth bound at batch size = 1 on NVIDIA GeForce RTX 3060 (12GB) (360 GB/s). Prompt prefill / TTFT (~711 tok/s) is compute-bound and utilizes GPU Tensor cores. Actual latency varies with FlashAttention-2 and runtime engine (Ollama/vLLM/llama.cpp).
Cloud Instance Options for Qwen 2.5 Coder 7B Instruct
On-DemandDeploy this model on an on-demand cloud GPU without local hardware constraints or power usage:
RunPod Cloud GPUsBest 1-Click Ollama & vLLM
$0.38/hr (RTX 4090 Spot) – $2.39/hr (H100)Vast.ai GPU MarketplaceCheapest Dual RTX 3090 / 4090
$0.18/hr (RTX 3060) – $0.78/hr (2x RTX 3090)Lambda GPU CloudEnterprise 8x H100 Clusters
$2.49/hr (H100) – $19.92/hr (8x H100)Quantization Precision Matrix
32K ctx • KV: Q8_0| Quantization | Weights | KV Cache | Total VRAM | Est. Speed | Fit Status |
|---|---|---|---|---|---|
| FP1616 bpw | 15.2 GB | 0.94 GB | 17.42 GB (145%) | 0 t/s | OOM |
| Q8_08.5 bpw | 8.06 GB | 0.94 GB | 10.03 GB (84%) | ~28 t/s | FITS |
| Q6_K6.56 bpw | 6.23 GB | 0.94 GB | 8.14 GB (68%) | ~36 t/s | FITS |
| Q5_K_M5.68 bpw | 5.4 GB | 0.94 GB | 7.28 GB (61%) | ~42 t/s | FITS |
| Q4_K_M4.8 bpw | 4.56 GB | 0.94 GB | 6.41 GB (53%) | ~49 t/s | FITS |
| FP44.25 bpw | 4.03 GB | 0.94 GB | 5.86 GB (49%) | ~55 t/s | FITS |
| IQ3_XS3.3 bpw | 3.12 GB | 0.94 GB | 4.92 GB (41%) | ~70 t/s | FITS |
Hardware Compatibility Matrix for Qwen 2.5 Coder 7B Instruct
Standard Q4_K_M precision with 32K context window and Q8_0 KV cache
| Hardware System | VRAM Envelope | Required VRAM | Headroom | Est. Decode Speed | Compatibility | Test Fit |
|---|---|---|---|---|---|---|
| NVIDIA GeForce RTX 5090 (32GB GDDR7) Consumer GPU • 1792 GB/s | 32 GB | 6.41 GB | +25.59 GB | ~254 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 4090 (24GB GDDR6X) Consumer GPU • 1008 GB/s | 24 GB | 6.41 GB | +17.59 GB | ~143 tok/s | ✓ FITS | Test Fit → |
| 2x NVIDIA RTX 3090 Dual Rig (48GB Total VRAM) Multi-GPU Rig • 1648 GB/s | 48 GB | 7.11 GB | +40.89 GB | ~213 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 5080 (16GB GDDR7) Consumer GPU • 960 GB/s | 16 GB | 6.41 GB | +9.59 GB | ~136 tok/s | ✓ FITS | Test Fit → |
| NVIDIA RTX 4070 Ti Super (16GB) Consumer GPU • 672 GB/s | 16 GB | 6.41 GB | +9.59 GB | ~94 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 3060 (12GB) Consumer GPU • 360 GB/s | 12 GB | 6.41 GB | +5.59 GB | ~49 tok/s | ✓ FITS | Test Fit → |
| Apple MacBook Pro/Air M1 (8GB Unified Memory) Apple Silicon • 68 GB/s | 7 GB | 6.41 GB | +0.59 GB | ~9 tok/s | • TIGHT FIT | Test Fit → |
| Apple MacBook Pro/Air (16GB Unified Memory) Apple Silicon • 100 GB/s | 14 GB | 6.41 GB | +7.59 GB | ~13 tok/s | ✓ FITS | Test Fit → |
| Apple MacBook Pro M4 Pro (24GB Unified Memory) Apple Silicon • 273 GB/s | 20 GB | 6.41 GB | +13.59 GB | ~36 tok/s | ✓ FITS | Test Fit → |
| Apple Mac Mini M4 Pro (64GB Unified Memory) Apple Silicon • 273 GB/s | 54 GB | 6.41 GB | +47.59 GB | ~36 tok/s | ✓ FITS | Test Fit → |
| Apple Mac Studio M4 Max (128GB Unified Memory) Apple Silicon • 546 GB/s | 112 GB | 6.41 GB | +105.59 GB | ~73 tok/s | ✓ FITS | Test Fit → |
| Apple Mac Studio M3 Ultra (256GB Unified Memory) Apple Silicon • 819 GB/s | 236 GB | 6.41 GB | +229.59 GB | ~109 tok/s | ✓ FITS | Test Fit → |
| AMD Strix Halo Mini-PC (Ryzen AI Max+ 395 128GB) Unified APU / Mini-PC • 256 GB/s | 110 GB | 6.41 GB | +103.59 GB | ~30 tok/s | ✓ FITS | Test Fit → |
| NVIDIA DGX Spark (128GB Grace-Blackwell Unified) AI Appliance • 273 GB/s | 118 GB | 6.41 GB | +111.59 GB | ~38 tok/s | ✓ FITS | Test Fit → |
| NVIDIA H100 SXM (80GB HBM3 Cloud GPU) Datacenter Cloud GPU • 3350 GB/s | 80 GB | 6.41 GB | +73.59 GB | ~503 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 5070 Ti (16GB GDDR7) Consumer GPU • 896 GB/s | 16 GB | 6.41 GB | +9.59 GB | ~127 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 5070 (12GB GDDR7) Consumer GPU • 672 GB/s | 12 GB | 6.41 GB | +5.59 GB | ~95 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 4080 Super (16GB GDDR6X) Consumer GPU • 736 GB/s | 16 GB | 6.41 GB | +9.59 GB | ~104 tok/s | ✓ FITS | Test Fit → |
| AMD Radeon RX 7900 XTX (24GB GDDR6) Consumer GPU • 960 GB/s | 24 GB | 6.41 GB | +17.59 GB | ~116 tok/s | ✓ FITS | Test Fit → |
| AMD Radeon RX 7900 XT (20GB GDDR6) Consumer GPU • 800 GB/s | 20 GB | 6.41 GB | +13.59 GB | ~97 tok/s | ✓ FITS | Test Fit → |
| Apple Mac Studio M2 Ultra (192GB Unified Memory) Apple Silicon Workstation • 800 GB/s | 144 GB | 6.41 GB | +137.59 GB | ~108 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 3090 (24GB GDDR6X) Consumer GPU • 936 GB/s | 24 GB | 6.41 GB | +17.59 GB | ~127 tok/s | ✓ FITS | Test Fit → |
| NVIDIA GeForce RTX 4060 Ti (16GB GDDR6) Consumer GPU • 288 GB/s | 16 GB | 6.41 GB | +9.59 GB | ~39 tok/s | ✓ FITS | Test Fit → |
| Apple Mac Mini M4 (16GB Unified Memory) Apple Silicon • 120 GB/s | 13 GB | 6.41 GB | +6.59 GB | ~15 tok/s | ✓ FITS | Test Fit → |
| Apple Mac Mini M4 (24GB Unified Memory) Apple Silicon • 120 GB/s | 20 GB | 6.41 GB | +13.59 GB | ~15 tok/s | ✓ FITS | Test Fit → |