OLMo 2 7B needs ~7.9 GB VRAM. RTX 3050 8GB has 8.0 GB. With Q4_K_M quantization, expect ~31 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 with offload
Decode
31.3 tok/s
TTFT
6192 ms
Safe context
4K
Memory
7.9 GB / 8.0 GB
This setup is broadly balanced for this model.
Very little memory headroom
You can run the model, but there is not much room left for longer context, bigger batches, extra apps, or future model updates.
Buy headroom, not only minimum fit
A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
| Workload | Grade | Fit | Decode | TTFT | Context |
|---|---|---|---|---|---|
| Chat | A | Tight fit | 31.3 tok/s | 3378 ms | 4K |
| Coding | A | Runs with offload | 31.3 tok/s | 6192 ms | 4K |
| Agentic Coding | F | Too heavy | 15.0 tok/s | 18712 ms | 4K |
| Reasoning | A | Runs with offload | 31.3 tok/s | 7318 ms | 4K |
| RAG | F | Too heavy | 15.0 tok/s | 23391 ms | 4K |
How OLMo 2 7B (7B params) fits at each quantization level on RTX 3050 8GB (8.0 GB usable).
| Quant | Bits | VRAM | Quality | Fit |
|---|---|---|---|---|
Q2_K | 2 | 2.7 GB | Low | A74 |
Q3_K_S | 3 | 3.4 GB | Low | A74 |
NVFP4 | 4 | 3.9 GB | Medium | A74 |
Q4_K_M | 4 | 4.3 GB | Medium | A74 |
Q5_K_MBest for your GPU | 5 | 5.0 GB | High | A73 |
Q6_K | 6 | 5.7 GB | High | F0 |
Q8_0 | 8 | 7.5 GB | Very High | F0 |
F16 | 16 | 14.3 GB | Maximum | F0 |
Copy-paste commands to run OLMo 2 7B on your machine.
Run
ollama run olmo2:7bYour hardware
| Model | Params | Grade | Decode | Capabilities |
|---|---|---|---|---|
 Qwen 3.5 9B | 9B | A | 13.3 tok/s | |
| Qwen 3 8B | 8B | A | 14.5 tok/s | |
 Nemotron Nano 8B | 8B | A | 17.9 tok/s | |
 InternVL2 8B | 8B | A | 17.9 tok/s | |
 Ministral 3 8B | 8B | B | 16.9 tok/s |
Yes, RTX 3050 8GB can run OLMo 2 7B with a A grade (Runs with offload). Expected decode speed: 31.3 tok/s.
OLMo 2 7B (7B parameters) requires approximately 7.9 GB of memory with Q4_K_M quantization.
The recommended quantization for OLMo 2 7B is Q4_K_M, which balances quality and memory efficiency.
On RTX 3050 8GB, OLMo 2 7B achieves approximately 31.3 tokens per second decode speed with a time-to-first-token of 6192ms using Q4_K_M quantization.
For coding workloads, OLMo 2 7B on RTX 3050 8GB receives a A grade with 31.3 tok/s and 4K context.
On RTX 3050 8GB, OLMo 2 7B can safely use up to 4K tokens of context. The model's official context limit is 4K, but available memory constrains the safe maximum.
Buy headroom, not only minimum fit. A slightly larger memory tier gives you safer context growth and makes the recommendation more future-proof.
Paste this snippet into any page to show a live fit card.
<iframe src="https://willitrunai.com/embed/olmo-2-7b-on-rtx-3050-8gb" width="400" height="180" frameborder="0" style="border:none;border-radius:12px;overflow:hidden;" title="Will It Run AI — fit result"></iframe>
Preview: