MacBook Pro M4 Pro 24GB经济之选
24 GB Unified (+8)
B
This setup is broadly balanced for this model.48.7 tok/s 解码
~$1,999 MSRP
Can Mistral 7B Instruct v0.3 run on RTX 4060 Ti 16GB?
YES — Runs Great
B64Good
Estimated from fit model
Mistral 7B Instruct v0.3 needs ~9.0 GB VRAM. RTX 4060 Ti 16GB has 16.0 GB. With Q4_K_M quantization, expect ~53 tok/s.
Runtime: OllamaCapacity: RoomyBandwidth: LowStack: BasicBottleneck: Balanced
Operating mode
Choose the run profile you care about
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
Q4_K_M (Medium quality) — 9.0 GB, 52.9 tok/s, Runs well
9.0 GB required16.0 GB available
56% VRAM used
Fit status
Runs well
Decode
52.9 tok/s
TTFT
3658 ms
Safe context
8K
Memory
9.0 GB / 16.0 GB
Memory breakdown
Weights4.3 GB
KV Cache2.0 GB
Runtime1.2 GB
Headroom1.6 GB
See how fast it feels
See how fast it feelsMistral 7B Instruct v0.3 on RTX 4060 Ti 16GB
1st promptCold start — includes initialization
>Solve: If a train travels at 60 mph for 2.5 hours, how far does it go?
Let me work through this step by step.
Given information:
- Speed = 60 mph (miles per hour)
- Time = 2.5 hours
Formula: Distance = Speed x Time
Calculation:
Distance = 60 mph x 2.5 h
= 150 miles
The train travels 150 miles.
Double-check: at 60 mph the train covers 60 miles each hour. In half an hour it covers 30 miles. So in 2.5 hours: 60 + 60 + 30 = 150 miles. Confirmed.
2nd promptWarm — model ready, no init overhead
>What if the train stops for 20 minutes halfway?
The stop doesn't change the total distance covered while moving, but it affects total trip time.
Breakdown:
- First half: 1.25 hours at 60 mph = 75 miles
- Stop: 20 minutes (no distance)
- Second half: 1.25 hours at 60 mph = 75 miles
Total distance: 150 miles (same)
Total time: 2.5 h + 0.33 h = 2.83 hours
Average speed: 150 / 2.83 = 53 mph
The distance stays the same but average speed drops to 53 mph because of the stop.
Estimated: 52.9 tok/s decode · 3.7s TTFT (warm) · 132 tok/s prefill
What limits this setup
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best improvement path
Performance by workload
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | B | Runs well | 52.9 tok/s | 1995 ms | 8K |
| Coding | B | Runs well | 52.9 tok/s | 3658 ms | 8K |
| Agentic Coding | B | Runs well | 52.9 tok/s | 5320 ms | 8K |
| Reasoning | B | Runs well | 52.9 tok/s | 4323 ms | 8K |
| RAG | B | Runs well | 52.9 tok/s | 6650 ms | 8K |
Quantization options
How Mistral 7B Instruct v0.3 (7B params) fits at each quantization level on RTX 4060 Ti 16GB (16.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | B59 |
Q3_K_S | 3 | 3.4 GB | Low | B60 |
NVFP4 | 4 | 3.9 GB | Medium | B60 |
Q4_K_M | 4 | 4.3 GB | Medium | B60 |
Q5_K_M | 5 | 5.0 GB | High | B61 |
Q6_K | 6 | 5.7 GB | High | B62 |
Q8_0Best for your GPU | 8 | 7.5 GB | Very High | B64 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Get started
Copy-paste commands to run Mistral 7B Instruct v0.3 on your machine.
Run
lms load Mistral-7B-Instruct-v0.3 && lms server start升级选项
能流畅运行 Mistral 7B Instruct v0.3 的硬件
Frequently asked questions
Can RTX 4060 Ti 16GB run Mistral 7B Instruct v0.3?
Yes, RTX 4060 Ti 16GB can run Mistral 7B Instruct v0.3 with a B grade (Runs well). Expected decode speed: 52.9 tok/s.
How much VRAM does Mistral 7B Instruct v0.3 need?
Mistral 7B Instruct v0.3 (7B parameters) requires approximately 9.0 GB of memory with Q4_K_M quantization.
What is the best quantization for Mistral 7B Instruct v0.3?
The recommended quantization for Mistral 7B Instruct v0.3 is Q4_K_M, which balances quality and memory efficiency.
What speed will Mistral 7B Instruct v0.3 run at on RTX 4060 Ti 16GB?
On RTX 4060 Ti 16GB, Mistral 7B Instruct v0.3 achieves approximately 52.9 tokens per second decode speed with a time-to-first-token of 3658ms using Q4_K_M quantization.
Can RTX 4060 Ti 16GB run Mistral 7B Instruct v0.3 for coding?
For coding workloads, Mistral 7B Instruct v0.3 on RTX 4060 Ti 16GB receives a B grade with 52.9 tok/s and 8K context.
What context window can Mistral 7B Instruct v0.3 use on RTX 4060 Ti 16GB?
On RTX 4060 Ti 16GB, Mistral 7B Instruct v0.3 can safely use up to 8K tokens of context. The model's official context limit is 8K, but available memory constrains the safe maximum.
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