OLMoE 1B 7B 0924 — Hardware Requirements & GPU Compatibility
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OLMoE 1B 7B 0924 is a 6.9B-parameter open language model from Allen AI in the OLMo family. It supports a context window of up to 4,096 tokens. At Q4_K_M it needs about 4.72 GB of VRAM — see which GPUs and Macs can run it below.
172.0K downloads
146 likesSpecifications
- Publisher
- Allen AI
- Family
- OLMo
- Parameters
- 6.9B
- Architecture
- OlmoeForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 50,304
- Release Date
- 2024-07-20
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does OLMoE 1B 7B 0924 Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 3.5 GB | 3.8 GB | 2.94 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 3.6 GB | 3.9 GB | 3.03 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 3.9 GB | 4.2 GB | 3.37 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 4.0 GB | 4.3 GB | 3.46 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 4.7 GB | 5.0 GB | 4.15 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 5.5 GB | 5.8 GB | 4.93 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 6.3 GB | 6.5 GB | 5.71 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 7.5 GB | 7.8 GB | 6.92 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 OLMoE 1B 7B 0924?
Q4_K_M · 4.7 GBOLMoE 1B 7B 0924 (Q4_K_M) requires 4.7 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 7+ GB is recommended. Using the full 4K context window can add up to 0.3 GB, bringing total usage to 5.0 GB. 50 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run OLMoE 1B 7B 0924?
Q4_K_M · 4.7 GB59 devices with unified memory can run OLMoE 1B 7B 0924, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Apple iPhone 17 Pro.
Runs great
— Plenty of headroom
Decent
— Enough memory, may be tightWhere to Download OLMoE 1B 7B 0924
Community quantizations of this model — GGUF for llama.cpp, Ollama, and LM Studio, plus AWQ/MLX variants where available.
Related Models
Frequently Asked Questions
- How much VRAM does OLMoE 1B 7B 0924 need?
OLMoE 1B 7B 0924 requires 4.7 GB of VRAM at Q4_K_M, or 14.4 GB at BF16.
VRAM = Weights + KV Cache + Overhead
Weights = 6.9B × 4.8 bits ÷ 8 = 4.2 GB
KV Cache + Overhead ≈ 0.5 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 0.8 GB (at full 4K context)
VRAM usage by quantization
Q4_K_M4.7 GBQ4_K_M + full context5.0 GB- What's the best quantization for OLMoE 1B 7B 0924?
For OLMoE 1B 7B 0924, Q4_K_M (4.7 GB) offers the best balance of quality and VRAM usage. Q5_0 (4.9 GB) provides better quality if you have the VRAM. The smallest option is Q2_K at 3.5 GB.
VRAM requirement by quantization
Q2_K3.5 GBQ4_04.0 GBQ4_K_M ★4.7 GBQ5_04.9 GBQ5_K_M5.5 GBBF1614.4 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run OLMoE 1B 7B 0924 on a Mac?
OLMoE 1B 7B 0924 requires at least 3.5 GB at Q2_K, 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 OLMoE 1B 7B 0924 locally?
Yes — OLMoE 1B 7B 0924 can run locally on consumer hardware. At Q4_K_M quantization it needs 4.7 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is OLMoE 1B 7B 0924?
At Q4_K_M, OLMoE 1B 7B 0924 can reach ~932 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~139 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 ÷ 4.7 × 0.65 = ~1102 tok/s
Estimated speed at Q4_K_M (4.7 GB)
~1102 tok/s~139 tok/s~1102 tok/s~932 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of OLMoE 1B 7B 0924?
At Q4_K_M, the download is about 4.15 GB. The full-precision BF16 version is 13.84 GB. The smallest option (Q2_K) is 2.94 GB.
- Which GPUs can run OLMoE 1B 7B 0924?
50 consumer GPUs can run OLMoE 1B 7B 0924 at Q4_K_M (4.7 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 50 GPUs have plenty of headroom for comfortable inference.
- Which devices can run OLMoE 1B 7B 0924?
59 devices with unified memory can run OLMoE 1B 7B 0924 at Q4_K_M (4.7 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.