OLMo 3 7B Think · 4 GPUs measured first-party · llama.cpp · Updated October 2026
OLMo 3 7B Think on 4 GPUs, measured first-party: NVIDIA GeForce RTX 5090 leads at 266.7 tok/s, RTX 4060 Ti 16GB trails at 58.3 tok/s, and it peaked at 5GB of VRAM.
Benchmarked weights: unsloth/Olmo-3-7B-Think-GGUF

266.7 tok/s on OLMo 3 7B Think, the ceiling. Measured on our bench. 32GB of VRAM, $1,999 at launch.

170.7 tok/s on OLMo 3 7B Think, fastest card you can buy at retail. Measured on our bench. 24GB of VRAM, $1,599 at launch.

69.18 tok/s on OLMo 3 7B Think, lowest launch price that still fits. Measured on our bench. 12GB of VRAM, $329 at launch.

58.29 tok/s on OLMo 3 7B Think, most speed per dollar. Measured on our bench. 16GB of VRAM, $499 at launch. That is 116.8 tok/s per $1,000 of launch price.
What GPU Do You Need for OLMo 3 7B Think?, tok/s by GPU
Efficiency: tok/s per 100W drawn
Power is the average pulled during the run, sampled at 1Hz. The fastest card is often not the one here, and for anything left running this is the number that shows up on the bill.
Value: tok/s per $1,000 of MSRP
Launch price, not street price, so it ages. A speed leaderboard always crowns the most expensive card; this is the counterweight.
OLMo 3 7B Think. Measured tokens per second by GPU
| GPU | tok/s | Prompt t/s | tok/W | Avg power |
|---|---|---|---|---|
| NVIDIA GeForce RTX 5090 | 266.7 | 14283 | 0.92 | 288.4 W |
| NVIDIA GeForce RTX 4090 | 170.7 | 11617.9 | 0.94 | 182.5 W |
| NVIDIA GeForce RTX 3060 | 69.18 | 2224.4 | 0.51 | 134.9 W |
| NVIDIA GeForce RTX 4060 Ti 16GB | 58.29 | 3636.3 | 0.54 | 107.1 W |
What the numbers show. Across 4 GPUs measured on our own bench, RTX 5090 is fastest at 267 tok/s. The slowest, RTX 4060 Ti 16GB, manages 58.3, so the spread is 4.6x from top to bottom. RTX 4090 is the most efficient, 171 tok/s at 182W. Per dollar of launch price, RTX 3060 gives the most (210.3 tok/s per $1,000). The fastest card with 16GB or less is RTX 3060 at 69.2 tok/s.
About OLMo 3 7B Think. OLMo 3 7B Think: from allenai, 7.3B parameters, on Hugging Face since November 2025, Apache 2.0 licence. 487,624 downloads in the last 30 days.
How it compares. RTX 5090: OLMo 3 7B Think 266.7 tok/s, OLMo 3 7B Instruct 266.7 (7B), Qwen2.5-7B 284.6 (8B), Qwen2.5-Coder 7B 284.6 (8B), Qwen2-7B-Instruct 277.6 (8B). 3 of 4 beat OLMo 3 7B Think here.
Cost on a rented GPU. 1M generated tokens of OLMo 3 7B Think: $0.14 on a RTX 3060 ($0.036/hr, 4.0 hours), $0.41 on a RTX 5090 ($0.39/hr, 62 min, 2.8x the cost).
OLMo 3 7B Think: cost per 1M generated tokens on rented GPUs
| GPU | Cheapest rate | Speed (tok/s) | Cost per 1M generated tokens |
|---|---|---|---|
| NVIDIA GeForce RTX 3060 | $0.036/hr | 69.18 | $0.14 |
| NVIDIA GeForce RTX 5090 | $0.39/hr | 266.7 | $0.41 |
| NVIDIA GeForce RTX 4090 | $0.34/hr | 170.7 | $0.55 |
Cheapest hourly rate we track on RunPod and Vast.ai, divided by the measured speed. Startup time and storage are extra.
Speed tiers for OLMo 3 7B Think. 30+ tok/s: 4 (RTX 5090, RTX 4090, RTX 3060). 30 tok/s is roughly where replies outpace reading.
Reading your prompt. Before OLMo 3 7B Think writes anything it reads the input: 14283.0 tok/s on the RTX 5090 (0.3s for a 4,000-token prompt), 11617.9 on the RTX 4090 (0.3s), 2224.4 on the RTX 3060 (1.8s). Long documents and big code files feel this number more than the generation speed.
VRAM for OLMo 3 7B Think. Measured peak 4.6GB, so 8GB is the smallest common card size; smallest card it ran on: RTX 3060 (12GB). With long context: Q4_K_M 6GB (tested), Q2_K 4GB, Q3_K_M 5GB, Q5_K_M 7GB, Q6_K 9GB.
Power on OLMo 3 7B Think. Most efficient: RTX 4090, 182W, 0.30 kWh per 1M generated tokens. Hungriest: RTX 5090, 288W, 0.30 kWh. At $0.15/kWh: $0.045 per 1M generated tokens.
Fastest on OLMo 3 7B Think: NVIDIA GeForce RTX 5090, 266.7 tok/s. Cheapest consumer card that ran it: NVIDIA GeForce RTX 3060 ($329, 69.18 tok/s). Cheapest to rent per job: NVIDIA GeForce RTX 3060, $0.14 per 1M generated tokens.
llama.cpp llama-bench at Q4_K_M, 512-token prompt and 128 generated tokens, three runs after a warmup, full GPU offload, with power and VRAM sampled throughout. Token generation is memory-bandwidth-bound, so the ranking tracks bandwidth closely, which makes it a fair guide to cards we haven't run yet.