OLMoE 1B 7B 0125 Instruct — Hardware Requirements & GPU Compatibility
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OLMoE 1B 7B 0125 Instruct is a 6.9B-parameter open language model from Allen AI. 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.
102.2K downloads
65 likesSpecifications
- Publisher
- Allen AI
- Parameters
- 6.9B
- Architecture
- OlmoeForCausalLM
- Context Length
- 4,096 tokens
- Vocabulary Size
- 50,304
- Release Date
- 2025-02-04
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does OLMoE 1B 7B 0125 Instruct 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 |
Which GPUs Can Run OLMoE 1B 7B 0125 Instruct?
Q4_K_M · 4.7 GBOLMoE 1B 7B 0125 Instruct (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. 35 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 0125 Instruct?
Q4_K_M · 4.7 GB33 devices with unified memory can run OLMoE 1B 7B 0125 Instruct, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Derivatives (3)
Frequently Asked Questions
- How much VRAM does OLMoE 1B 7B 0125 Instruct need?
OLMoE 1B 7B 0125 Instruct requires 4.7 GB of VRAM at Q4_K_M, or 7.5 GB at Q8_0.
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 0125 Instruct?
For OLMoE 1B 7B 0125 Instruct, Q4_K_M (4.7 GB) offers the best balance of quality and VRAM usage. Q5_K_S (5.3 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 2.5 GB.
VRAM requirement by quantization
IQ2_XXS2.5 GBIQ3_XS3.4 GBQ3_K_M3.9 GBIQ4_NL4.5 GBQ4_K_M ★4.7 GBQ8_07.5 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run OLMoE 1B 7B 0125 Instruct on a Mac?
OLMoE 1B 7B 0125 Instruct requires at least 2.5 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 OLMoE 1B 7B 0125 Instruct locally?
Yes — OLMoE 1B 7B 0125 Instruct 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 0125 Instruct?
At Q4_K_M, OLMoE 1B 7B 0125 Instruct can reach ~618 tok/s on AMD Instinct MI300X. 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: AMD Instinct MI300X → 5300 ÷ 4.7 × 0.55 = ~618 tok/s
Estimated speed at Q4_K_M (4.7 GB)
~618 tok/s~139 tok/s~462 tok/s~382 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 0125 Instruct?
At Q4_K_M, the download is about 4.15 GB. The full-precision Q8_0 version is 6.92 GB. The smallest option (IQ2_XXS) is 1.90 GB.
- Which GPUs can run OLMoE 1B 7B 0125 Instruct?
35 consumer GPUs can run OLMoE 1B 7B 0125 Instruct at Q4_K_M (4.7 GB). Top options include AMD Radeon RX 6700 XT, AMD Radeon RX 6800, AMD Radeon RX 6800 XT. 35 GPUs have plenty of headroom for comfortable inference.
- Which devices can run OLMoE 1B 7B 0125 Instruct?
33 devices with unified memory can run OLMoE 1B 7B 0125 Instruct at Q4_K_M (4.7 GB), including Mac Mini M4 (16 GB), Mac Mini M4 (32 GB), Mac Mini M4 Pro (24 GB), Mac Mini M4 Pro (48 GB). Apple Silicon Macs use unified memory shared between CPU and GPU, making them well-suited for local LLM inference.