There’s a small army of on-device models coming to Chrome

1. ULM128M
2. LLMTI1B
3. GEMINI2_NANOV2
4. GEMINI2_NANOV2_EE2Q
5. GEMINI_XS
6. GEMINI_XS_DRAFTER_6LAYER_CAUSAL_USM_700M_RESIDUAL
7. GEMINI_XS_LUSM_700M_RESIDUAL_BOTTOM15
8. GEMINI2_NANOV2_EE12Q
9. GEMINI2_NANOV2_EE2_LUSM_700M
10. GEMINI2_NANOV2_CAUSAL_700M
11. GEMINI2_NANOV2_EE20_CAUSAL_LUSM_700M
12. GEMINI_XL_DRAFTER_24LAYER
13. GEMINI_XS_FA1
14. GEMMA2_8B
15. GEMMA2_7B
16. GEMMA2_2B
17. GEMMA3_1B
18. GEMMA3_4B
19. GEMMA3_12B
20. GEMMA3_27B
21. STABLELM_4E1T_3B_PHI_2_TF_LITE

1. ULM128M

• Interpretation:
  Likely a “Universal Language Model” with 128 million parameters. Common in smaller, efficient AI applications.

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2. LLMIT1B

• Interpretation:
  Large Language Model, Instruction-Tuned, 1 Billion parameters.
  • LLM: Large Language Model
  • IT: Instruction-Tuned (fine-tuned to follow human instructions for chat, Q&A, etc.)
  • 1B: 1 billion parameters
• Typical Use Case:
  A compact, efficient instruction-following model designed for conversational agents, chatbots, and smart assistants—optimized for inference speed while maintaining the ability to understand and follow complex user instructions.

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3. GEMINI2_NANOV2

• Interpretation:
  “Gemini2” refers to Google’s Gemini model, with “NanoV2” being its second, smallest/efficient “Nano” version.

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4. GEMINI2_NANOV2_EE2Q

• Interpretation:
  A variant of Gemini2 NanoV2, probably quantized to a lower precision (e.g., 2-bit or Q for quantized), or “EE” could mean “Edge-Enhanced.”

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5. GEMINI_XS

• Interpretation:
  “Gemini Extra Small”—likely the smallest, most efficient Gemini variant.

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6. GEMINI_XS_DRAFTER_6LAYER_CAUSAL_USM_700M_RESIDUAL

• Interpretation:
  • “XS Drafter” = Gemini Extra Small, used for drafting (possibly text generation).
  • “6Layer” = 6 transformer layers.
  • “Causal” = Unidirectional, like GPT.
  • “USM_700M” = Universal Sentence Model, 700M parameters.
  • “Residual” = Uses residual connections for better training/stability.

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7. GEMINI_XS_LUSM_700M_RESIDUAL_BOTTOM15

• Interpretation:
  Similar to above, but “LUSM” could be a variant of the universal model, and “BOTTOM15” may mean it’s using the bottom 15 layers (or some layer selection trick).

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8. GEMINI2_NANOV2_EE12Q

• Interpretation:
  Gemini2 NanoV2, probably with Edge-Enhanced (EE) features and “12Q” indicating quantization at 12 bits or a quantization scheme.

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9. GEMINI2_NANOV2_EE2_LUSM_700M

• Interpretation:
  Another Gemini2 NanoV2 variant with Edge-Enhanced 2, using a LUSM 700M parameter model.

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10. GEMINI2_NANOV2_CAUSAL_700M

• Interpretation:
  Gemini2 NanoV2, causal (unidirectional), with 700M parameters.

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11. GEMINI2_NANOV2_EE20_CAUSAL_LUSM_700M

• Interpretation:
  Gemini2 NanoV2, Edge-Enhanced 20 (version or setting), causal, LUSM, 700M parameters.

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12. GEMINI_XL_DRAFTER_24LAYER

• Interpretation:
  “XL” = Extra Large variant.
  “Drafter” = Possibly optimized for initial text generation or suggestion.
  “24Layer” = 24 transformer layers.

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13. GEMINI_XS_FA1

• Interpretation:
  Gemini Extra Small, “FA1” could be “Fast Architecture 1” or a specific feature set/version.

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14. GEMMA2_8B

• Interpretation:
  Gemma model, version 2, with 8 billion parameters.

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15. GEMMA2_7B

• Interpretation:
  Gemma version 2, 7 billion parameters.

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16. GEMMA2_2B

• Interpretation:
  Gemma version 2, 2 billion parameters.

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17. GEMMA3_1B

• Interpretation:
  Gemma version 3, 1 billion parameters.

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18. GEMMA3_4B

• Interpretation:
  Gemma version 3, 4 billion parameters.

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19. GEMMA3_12B

• Interpretation:
  Gemma version 3, 12 billion parameters.

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20. GEMMA3_27B

• Interpretation:
  Gemma version 3, 27 billion parameters.

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21. STABLELM_4E1T_3B_PHI_2_TF_LITE

• Interpretation:
  • “StableLM” = Stable Language Model (by Stability AI).
  • “4E1T” = Possibly a version or internal code.
  • “3B” = 3 billion parameters.
  • “PHI_2” = Possibly related to Microsoft’s Phi-2 model or a version.
  • “TF_LITE” = TensorFlow Lite (optimized for mobile/edge deployment).