OpenHermes 2.5 Mistral 7B — Hardware Requirements & GPU Compatibility
Chat
OpenHermes 2.5 is a community-driven fine-tune of Mistral 7B created by Teknium, trained on over 900,000 entries of high-quality synthetic data generated primarily by GPT-4. It quickly became one of the most popular open chat models of its era, consistently topping community benchmarks for 7B-class models. For local users, it offers strong instruction-following, creative writing, and coding assistance in a package that runs comfortably on a single consumer GPU with 8 GB of VRAM.
151.8K downloads
888 likesSpecifications
- Publisher
- Teknium
- Family
- Mistral
- Parameters
- 7B
- Architecture
- MistralForCausalLM
- Context Length
- 32,768 tokens
- Vocabulary Size
- 32,002
- Release Date
- 2024-02-19
- License
- Apache 2.0
Get Started
HuggingFace
How Much VRAM Does OpenHermes 2.5 Mistral 7B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 3.5 GB | 7.6 GB | 2.98 GB | 2-bit quantization with K-quant improvements |
| IQ3_S | 3.40 | 3.5 GB | 7.6 GB | 2.98 GB | Importance-weighted 3-bit, small |
| Q3_K_S | 3.50 | 3.6 GB | 7.7 GB | 3.06 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 4.0 GB | 8.0 GB | 3.41 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 4.1 GB | 8.1 GB | 3.50 GB | 4-bit legacy quantization |
| Q3_K_L | 4.10 | 4.2 GB | 8.2 GB | 3.59 GB | 3-bit large quantization |
| IQ4_XS | 4.30 | 4.3 GB | 8.4 GB | 3.76 GB | Importance-weighted 4-bit, compact |
| Q4_K_S | 4.50 | 4.5 GB | 8.5 GB | 3.94 GB | 4-bit small quantization |
| Q4_K_M | 4.80 | 4.8 GB | 8.8 GB | 4.20 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_0 | 5.00 | 4.9 GB | 9.0 GB | 4.38 GB | 5-bit legacy quantization |
| Q5_K_S | 5.50 | 5.4 GB | 9.4 GB | 4.81 GB | 5-bit small quantization |
| Q5_K_M | 5.70 | 5.6 GB | 9.6 GB | 4.99 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 6.3 GB | 10.4 GB | 5.78 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 7.6 GB | 11.6 GB | 7.00 GB | 8-bit quantization, near-lossless |
Which GPUs Can Run OpenHermes 2.5 Mistral 7B?
Q4_K_M · 4.8 GBOpenHermes 2.5 Mistral 7B (Q4_K_M) requires 4.8 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 33K context window can add up to 4.0 GB, bringing total usage to 8.8 GB. 35 GPUs can run it, including NVIDIA GeForce RTX 5090, NVIDIA GeForce RTX 3090 Ti.
Runs great
— Plenty of headroomWhich Devices Can Run OpenHermes 2.5 Mistral 7B?
Q4_K_M · 4.8 GB33 devices with unified memory can run OpenHermes 2.5 Mistral 7B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB.
Runs great
— Plenty of headroomRelated Models
Derivatives (5)
Frequently Asked Questions
- How much VRAM does OpenHermes 2.5 Mistral 7B need?
OpenHermes 2.5 Mistral 7B requires 4.8 GB of VRAM at Q4_K_M, or 7.6 GB at Q8_0. Full 33K context adds up to 4.0 GB (8.8 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 7B × 4.8 bits ÷ 8 = 4.2 GB
KV Cache + Overhead ≈ 0.6 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 4.6 GB (at full 33K context)
VRAM usage by quantization
Q4_K_M4.8 GBQ4_K_M + full context8.8 GB- What's the best quantization for OpenHermes 2.5 Mistral 7B?
For OpenHermes 2.5 Mistral 7B, Q4_K_M (4.8 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 GB~75%Q3_K_M4.0 GB~83%Q4_K_S4.5 GB~88%Q4_K_M ★4.8 GB~89%Q5_K_S5.4 GB~92%Q8_07.6 GB~99%★ Recommended — best balance of quality and VRAM usage.
- Can I run OpenHermes 2.5 Mistral 7B on a Mac?
OpenHermes 2.5 Mistral 7B 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 OpenHermes 2.5 Mistral 7B locally?
Yes — OpenHermes 2.5 Mistral 7B can run locally on consumer hardware. At Q4_K_M quantization it needs 4.8 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is OpenHermes 2.5 Mistral 7B?
At Q4_K_M, OpenHermes 2.5 Mistral 7B can reach ~611 tok/s on AMD Instinct MI300X. On NVIDIA GeForce RTX 4090: ~137 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 ÷ 4.8 × 0.55 = ~611 tok/s
Estimated speed at Q4_K_M (4.8 GB)
AMD Instinct MI300X~611 tok/sNVIDIA GeForce RTX 4090~137 tok/sNVIDIA H100 SXM~457 tok/sAMD Instinct MI250X~378 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of OpenHermes 2.5 Mistral 7B?
At Q4_K_M, the download is about 4.20 GB. The full-precision Q8_0 version is 7.00 GB. The smallest option (Q2_K) is 2.98 GB.