Olmo 3 1025 7B — Hardware Requirements & GPU Compatibility
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Olmo 3 1025 7B is a 7.3B-parameter open language model from Allen AI in the OLMo family. It supports a context window of up to 65,536 tokens. At Q4_K_M it needs about 5.75 GB of VRAM — see which GPUs and Macs can run it below.
123.4K downloads
79 likesSpecifications
- Publisher
- Allen AI
- Family
- OLMo
- Parameters
- 7.3B
- Architecture
- Olmo3ForCausalLM
- Context Length
- 65,536 tokens
- Vocabulary Size
- 100,278
- Release Date
- 2025-09-12
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does Olmo 3 1025 7B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 4.5 GB | 37.8 GB | 3.10 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 4.6 GB | 37.9 GB | 3.19 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 4.9 GB | 38.2 GB | 3.56 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 5.0 GB | 38.3 GB | 3.65 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 5.8 GB | 39.0 GB | 4.38 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 6.6 GB | 39.9 GB | 5.20 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 7.4 GB | 40.7 GB | 6.02 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 8.7 GB | 42.0 GB | 7.30 GB | 8-bit quantization, near-lossless |
est.= calculated VRAM estimate; no published GGUF file found for that quantization yet. Other rows are verified against real community uploads.
Which GPUs Can Run Olmo 3 1025 7B?
Q4_K_M · 5.8 GBOlmo 3 1025 7B (Q4_K_M) requires 5.8 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 8+ GB is recommended. Using the full 66K context window can add up to 33.3 GB, bringing total usage to 39.0 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti, NVIDIA GeForce RTX 3070 Ti.
Runs great
— Plenty of headroom
Decent
— Enough VRAM, may be tightWhich Devices Can Run Olmo 3 1025 7B?
Q4_K_M · 5.8 GB58 devices with unified memory can run Olmo 3 1025 7B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, MacBook Air 13" M3 (8 GB).
Runs great
— Plenty of headroomWhere to Download Olmo 3 1025 7B
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
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Frequently Asked Questions
- How much VRAM does Olmo 3 1025 7B need?
Olmo 3 1025 7B requires 5.8 GB of VRAM at Q4_K_M, or 16.0 GB at BF16. Full 66K context adds up to 33.3 GB (39.0 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 7.3B × 4.8 bits ÷ 8 = 4.4 GB
KV Cache + Overhead ≈ 1.3 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 34.6 GB (at full 66K context)
VRAM usage by quantization
Q4_K_M5.8 GBQ4_K_M + full context39.0 GB- What's the best quantization for Olmo 3 1025 7B?
For Olmo 3 1025 7B, Q4_K_M (5.8 GB) offers the best balance of quality and VRAM usage. Q5_K_S (6.4 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 3.4 GB.
VRAM requirement by quantization
IQ2_XXS3.4 GBIQ3_XS4.4 GBQ4_05.0 GBIQ4_NL5.5 GBQ4_K_M ★5.8 GBBF1616.0 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Olmo 3 1025 7B on a Mac?
Olmo 3 1025 7B requires at least 3.4 GB at IQ2_XXS, which exceeds the unified memory of most consumer Macs. You would need a Mac Studio or Mac Pro with a high-memory configuration.
- Can I run Olmo 3 1025 7B locally?
Yes — Olmo 3 1025 7B can run locally on consumer hardware. At Q4_K_M quantization it needs 5.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Olmo 3 1025 7B?
At Q4_K_M, Olmo 3 1025 7B can reach ~765 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~114 tok/s. Speed depends mainly on GPU memory bandwidth. Real-world results typically within ±20%.
tok/s = (bandwidth GB/s ÷ model GB) × efficiency
Example: NVIDIA B200 → 8000 ÷ 5.8 × 0.65 = ~904 tok/s
Estimated speed at Q4_K_M (5.8 GB)
~904 tok/s~114 tok/s~904 tok/s~765 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Olmo 3 1025 7B?
At Q4_K_M, the download is about 4.38 GB. The full-precision BF16 version is 14.60 GB. The smallest option (IQ2_XXS) is 2.01 GB.
- Which GPUs can run Olmo 3 1025 7B?
50 consumer GPUs can run Olmo 3 1025 7B at Q4_K_M (5.8 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT, AMD Radeon RX 7600. 39 GPUs have plenty of headroom for comfortable inference.
- Which devices can run Olmo 3 1025 7B?
59 devices with unified memory can run Olmo 3 1025 7B at Q4_K_M (5.8 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Apple iPhone 17 Pro, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.