Quick start
ollama run tinydolphin:latestRunnable variants
Memory is a rough file-size estimate; context length, runtime and GPU offload change it.
12 of 18 matching variants shown.18 of 18 variants shown.
| Tag | Type | Inputs | Digest | Download | Parameters | Quantization | Context | Est. memory | Run |
|---|---|---|---|---|---|---|---|---|---|
| 1.1b | Typelocal | Inputstext | Digest0f9dd11f824c | Download637 MB | Parameters1.1b | QuantizationUnknown | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b |
| 1.1b-v2.8-fp16 | Typelocal | Inputstext | Digestadb3e462abb8 | Download2.2 GB | Parameters1.1b | QuantizationFP16 | Context4K | Est. memory≈ 3.5 GB | ollama run tinydolphin:1.1b-v2.8-fp16 |
| 1.1b-v2.8-q2_K | Typelocal | Inputstext | Digest053ceac566b6 | Download432 MB | Parameters1.1b | QuantizationQ2_K | Context4K | Est. memory≈ 1.5 GB | ollama run tinydolphin:1.1b-v2.8-q2_K |
| 1.1b-v2.8-q3_K_L | Typelocal | Inputstext | Digestd744f6260a5a | Download592 MB | Parameters1.1b | QuantizationQ3_K_L | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q3_K_L |
| 1.1b-v2.8-q3_K_M | Typelocal | Inputstext | Digesta269253dc7d8 | Download548 MB | Parameters1.1b | QuantizationQ3_K_M | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q3_K_M |
| 1.1b-v2.8-q3_K_S | Typelocal | Inputstext | Digest1334375595f1 | Download499 MB | Parameters1.1b | QuantizationQ3_K_S | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q3_K_S |
| 1.1b-v2.8-q4_0 | Typelocal | Inputstext | Digest0f9dd11f824c | Download637 MB | Parameters1.1b | QuantizationQ4_0 | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q4_0 |
| 1.1b-v2.8-q4_1 | Typelocal | Inputstext | Digest3775322fd876 | Download701 MB | Parameters1.1b | QuantizationQ4_1 | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q4_1 |
| 1.1b-v2.8-q4_K_M | Typelocal | Inputstext | Digest0cf10b4bfdca | Download668 MB | Parameters1.1b | QuantizationQ4_K_M | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q4_K_M |
| 1.1b-v2.8-q4_K_S | Typelocal | Inputstext | Digest47eefa638255 | Download640 MB | Parameters1.1b | QuantizationQ4_K_S | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q4_K_S |
| 1.1b-v2.8-q5_0 | Typelocal | Inputstext | Digestbd9464ab8450 | Download766 MB | Parameters1.1b | QuantizationQ5_0 | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q5_0 |
| 1.1b-v2.8-q5_1 | Typelocal | Inputstext | Digest2a519cd98a34 | Download831 MB | Parameters1.1b | QuantizationQ5_1 | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q5_1 |
| 1.1b-v2.8-q5_K_M | Typelocal | Inputstext | Digest4a56f53dcad5 | Download782 MB | Parameters1.1b | QuantizationQ5_K_M | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q5_K_M |
| 1.1b-v2.8-q5_K_S | Typelocal | Inputstext | Digest635e25aae973 | Download766 MB | Parameters1.1b | QuantizationQ5_K_S | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:1.1b-v2.8-q5_K_S |
| 1.1b-v2.8-q6_K | Typelocal | Inputstext | Digest014f5ec4120f | Download903 MB | Parameters1.1b | QuantizationQ6_K | Context4K | Est. memory≈ 2.5 GB | ollama run tinydolphin:1.1b-v2.8-q6_K |
| 1.1b-v2.8-q8_0 | Typelocal | Inputstext | Digest852afb95a69e | Download1.2 GB | Parameters1.1b | QuantizationQ8_0 | Context4K | Est. memory≈ 2.5 GB | ollama run tinydolphin:1.1b-v2.8-q8_0 |
| latestdefault | Typelocal | Inputstext | Digest0f9dd11f824c | Download637 MB | ParametersUnknown | QuantizationUnknown | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:latest |
| v2.8 | Typelocal | Inputstext | Digest0f9dd11f824c | Download637 MB | ParametersUnknown | QuantizationUnknown | Context4K | Est. memory≈ 2 GB | ollama run tinydolphin:v2.8 |
Related models
The TinyLlama project is an open endeavor to train a compact 1.1B Llama model on 3 trillion tokens.
Granite 4 features improved instruction following (IF) and tool-calling capabilities, making them more effective in enterprise applications.
The IBM Granite 1B and 3B models are the first mixture of experts (MoE) Granite models from IBM designed for low latency usage.
Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models.