Dolphin 2.9.1 Yi 1.5 34B — Hardware Requirements & GPU Compatibility
Chat
Dolphin 2.9.1 Yi 1.5 34B is a 34.4-billion parameter chat model created by Eric Hartford's Dolphin project, fine-tuned from 01.AI's Yi 1.5 34B base. The Dolphin series is known for producing uncensored fine-tunes that remove alignment-based refusals, giving users more direct and unrestricted model responses. This model combines the strong bilingual capabilities of Yi 1.5 with Dolphin's open fine-tuning approach. It requires a GPU with at least 24GB of VRAM for quantized local inference and is popular among users who prefer models without built-in content restrictions.
4.7M downloads
57 likesSpecifications
- Publisher
- dphn
- Family
- Phi
- Parameters
- 34.4B
- Architecture
- LlamaForCausalLM
- Context Length
- 8,192 tokens
- Vocabulary Size
- 64,000
- Release Date
- 2024-05-18
- License
- Apache 2.0
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HuggingFace
How Much VRAM Does Dolphin 2.9.1 Yi 1.5 34B Need?
Select a quantization to see compatible GPUs below.
| Quantization | Bits | VRAM | + Context | File Size | Quality |
|---|---|---|---|---|---|
| Q2_K | 3.40 | 15.4 GB | 16.9 GB | 14.62 GB | 2-bit quantization with K-quant improvements |
| Q3_K_S | 3.50 | 15.8 GB | 17.4 GB | 15.05 GB | 3-bit small quantization |
| Q3_K_M | 3.90 | 17.6 GB | 19.1 GB | 16.76 GB | 3-bit medium quantization |
| Q4_0 | 4.00 | 18 GB | 19.5 GB | 17.19 GB | 4-bit legacy quantization |
| Q4_K_M | 4.80 | 21.4 GB | 22.9 GB | 20.63 GB | 4-bit medium quantization — most popular sweet spot |
| Q5_K_M | 5.70 | 25.3 GB | 26.8 GB | 24.50 GB | 5-bit medium quantization — good quality/size tradeoff |
| Q6_K | 6.60 | 29.2 GB | 30.7 GB | 28.37 GB | 6-bit quantization, very good quality |
| Q8_0 | 8.00 | 35.2 GB | 36.7 GB | 34.39 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 Dolphin 2.9.1 Yi 1.5 34B?
Q4_K_M · 21.4 GBDolphin 2.9.1 Yi 1.5 34B (Q4_K_M) requires 21.4 GB of VRAM to load the model weights. For comfortable inference with headroom for KV cache and system overhead, 28+ GB is recommended. Using the full 8K context window can add up to 1.5 GB, bringing total usage to 22.9 GB. 7 GPUs can run it, including NVIDIA GeForce RTX 5090.
All compatible consumer-level GPUs are running near their VRAM limit. You may also want to consider professional GPUs (e.g., NVIDIA A100, H100) which offer significantly more VRAM. For more headroom and better throughput, consider a multi-GPU configuration with tensor parallelism (supported by tools like vLLM, llama.cpp, or text-generation-inference).
Which Devices Can Run Dolphin 2.9.1 Yi 1.5 34B?
Q4_K_M · 21.4 GB41 devices with unified memory can run Dolphin 2.9.1 Yi 1.5 34B, including NVIDIA DGX H100, NVIDIA DGX A100 640GB, Mac Mini M4 Pro (24 GB).
Runs great
— Plenty of headroomDecent
— Enough memory, may be tightWhere to Download Dolphin 2.9.1 Yi 1.5 34B
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 Dolphin 2.9.1 Yi 1.5 34B need?
Dolphin 2.9.1 Yi 1.5 34B requires 21.4 GB of VRAM at Q4_K_M, or 69.6 GB at BF16. Full 8K context adds up to 1.5 GB (22.9 GB total).
VRAM = Weights + KV Cache + Overhead
Weights = 34.4B × 4.8 bits ÷ 8 = 20.6 GB
KV Cache + Overhead ≈ 0.8 GB (at 2K context + ~0.3 GB framework)
KV Cache + Overhead ≈ 2.3 GB (at full 8K context)
VRAM usage by quantization
Q4_K_M21.4 GBQ4_K_M + full context22.9 GB- Can NVIDIA GeForce RTX 4090 run Dolphin 2.9.1 Yi 1.5 34B?
Yes, at Q4_K_M (21.4 GB) or lower. Higher quantizations like Q5_K_S (24.4 GB) exceed the NVIDIA GeForce RTX 4090's 24 GB.
- What's the best quantization for Dolphin 2.9.1 Yi 1.5 34B?
For Dolphin 2.9.1 Yi 1.5 34B, Q4_K_M (21.4 GB) offers the best balance of quality and VRAM usage. Q5_K_S (24.4 GB) provides better quality if you have the VRAM. The smallest option is IQ2_XXS at 10.3 GB.
VRAM requirement by quantization
IQ2_XXS10.3 GBIQ3_XS15.0 GBQ3_K_M17.6 GBQ4_K_M ★21.4 GBQ5_K_S24.4 GBBF1669.6 GB★ Recommended — best balance of quality and VRAM usage.
- Can I run Dolphin 2.9.1 Yi 1.5 34B on a Mac?
Dolphin 2.9.1 Yi 1.5 34B requires at least 10.3 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 Dolphin 2.9.1 Yi 1.5 34B locally?
Yes — Dolphin 2.9.1 Yi 1.5 34B can run locally on consumer hardware. At Q4_K_M quantization it needs 21.4 GB of VRAM. Popular tools include Ollama, LM Studio, and llama.cpp.
- How fast is Dolphin 2.9.1 Yi 1.5 34B?
At Q4_K_M, Dolphin 2.9.1 Yi 1.5 34B can reach ~205 tok/s on AMD Instinct MI350X. On NVIDIA GeForce RTX 4090: ~31 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 ÷ 21.4 × 0.65 = ~243 tok/s
Estimated speed at Q4_K_M (21.4 GB)
~243 tok/s~31 tok/s~243 tok/s~205 tok/sReal-world results typically within ±20%. Speed depends on batch size, quantization kernel, and software stack.
- What's the download size of Dolphin 2.9.1 Yi 1.5 34B?
At Q4_K_M, the download is about 20.63 GB. The full-precision BF16 version is 68.78 GB. The smallest option (IQ2_XXS) is 9.46 GB.
- Which GPUs can run Dolphin 2.9.1 Yi 1.5 34B?
7 consumer GPUs can run Dolphin 2.9.1 Yi 1.5 34B at Q4_K_M (21.4 GB). Top options include AMD Radeon RX 7900 XTX, NVIDIA GeForce RTX 3090.
- Which devices can run Dolphin 2.9.1 Yi 1.5 34B?
41 devices with unified memory can run Dolphin 2.9.1 Yi 1.5 34B at Q4_K_M (21.4 GB), including AMD Ryzen AI 9 HX 370 (Strix Point) Laptop, ASUS Ascent GX10, Asus ROG Flow Z13 (2025, Ryzen AI Max+ 395, 128 GB), Beelink GTR9 Pro (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.