Collection

Google

54 model catalog entries

Googlegoogle/codegemma-1.1-7b

google/codegemma-1.1-7b

inspect — the catalog entry

{
  "id": "google/codegemma-1.1-7b",
  "name": "google/codegemma-1.1-7b",
  "description": "",
  "context_length": null
}

openrouter.ai/google/codegemma-1.1-7b

google/codegemma-7b

Googlegoogle/codegemma-7b

google/codegemma-7b

inspect — the catalog entry

{
  "id": "google/codegemma-7b",
  "name": "google/codegemma-7b",
  "description": "",
  "context_length": null
}

openrouter.ai/google/codegemma-7b

google/deplot

Googlegoogle/deplot

google/deplot

inspect — the catalog entry

{
  "id": "google/deplot",
  "name": "google/deplot",
  "description": "",
  "context_length": null
}

openrouter.ai/google/deplot

diffusiongemma-26b-a4b-it

Googlediffusiongemma-26b-a4b-it

google/diffusiongemma-26b-a4b-it

Diffusion-based 26B parameter LLM enabling parallel token generation for real-time text apps

inspect — the catalog entry

{
  "name": "diffusiongemma-26b-a4b-it",
  "publisher": "google",
  "labels": [
    "chat",
    "diffusion-llm",
    "text-to-text",
    "reasoning",
    "Download Available",
    "Free Endpoint"
  ],
  "attributes": {
    "AVAILABLE": "true",
    "last_month_download_count": "7491",
    "lastMonthApiInvocationCount": "421753",
    "lastMonthDownloadCount": "7479",
    "logo": "https://assets.ngc.nvidia.com/products/api-catalog/images/diffusiongemma-26b-a4b-it.jpg",
    "PREVIEW": "true",
    "last_month_api_invocation_count": "910230"
  },
  "id": "google/diffusiongemma-26b-a4b-it",
  "description": "Diffusion-based 26B parameter LLM enabling parallel token generation for real-time text apps",
  "context_length": null
}

openrouter.ai/google/diffusiongemma-26b-a4b-it

google/gemma-2b

Googlegoogle/gemma-2b

google/gemma-2b

inspect — the catalog entry

{
  "id": "google/gemma-2b",
  "name": "google/gemma-2b",
  "description": "",
  "context_length": null
}

openrouter.ai/google/gemma-2b

google/gemma-3-12b-it

Googlegoogle/gemma-3-12b-it

google/gemma-3-12b-it

inspect — the catalog entry

{
  "id": "google/gemma-3-12b-it",
  "name": "google/gemma-3-12b-it",
  "description": "",
  "context_length": null
}

openrouter.ai/google/gemma-3-12b-it

google/gemma-3-4b-it

Googlegoogle/gemma-3-4b-it

google/gemma-3-4b-it

inspect — the catalog entry

{
  "id": "google/gemma-3-4b-it",
  "name": "google/gemma-3-4b-it",
  "description": "",
  "context_length": null
}

openrouter.ai/google/gemma-3-4b-it

gemma-4-31b-it

Googlegemma-4-31b-it

google/gemma-4-31b-it

Dense 31B model delivering frontier reasoning for coding, agentic workflows, and fine-tuning.

inspect — the catalog entry

{
  "name": "gemma-4-31b-it",
  "publisher": "google",
  "labels": [
    "B200",
    "Together AI",
    "Fireworks AI",
    "reasoning",
    "CoreWeave",
    "GB300",
    "GB200",
    "Deepinfra",
    "coding",
    "chat",
    "text-to-text",
    "RTX PRO 6000 Blackwell Server Edition",
    "H200",
    "Download Available",
    "Partner Endpoint",
    "L40S",
    "Free Endpoint",
    "OpenRouter",
    "GMI Cloud",
    "agentic",
    "B300 SXM6 AC",
    "H100 80GB HBM3"
  ],
  "attributes": {
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    "last_month_download_count": "300083",
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    "PREVIEW": "true",
    "last_month_api_invocation_count": "406635"
  },
  "id": "google/gemma-4-31b-it",
  "description": "Dense 31B model delivering frontier reasoning for coding, agentic workflows, and fine-tuning.",
  "context_length": null
}

openrouter.ai/google/gemma-4-31b-it

google/recurrentgemma-2b

Googlegoogle/recurrentgemma-2b

google/recurrentgemma-2b

inspect — the catalog entry

{
  "id": "google/recurrentgemma-2b",
  "name": "google/recurrentgemma-2b",
  "description": "",
  "context_length": null
}

openrouter.ai/google/recurrentgemma-2b

paligemma

Googlepaligemma

google/google-paligemma

Vision language model adept at comprehending text and visual inputs to produce informative responses

inspect — the catalog entry

{
  "name": "paligemma",
  "publisher": "google",
  "labels": [
    "image",
    "cv",
    "Vision Assistant",
    "Image-to-Text",
    "vlm",
    "Visual Question Answering",
    "computer vision",
    "Language Generation",
    "video",
    "Free Endpoint"
  ],
  "attributes": {
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    "lastMonthApiInvocationCount": "2081",
    "lastMonthDownloadCount": "0",
    "logo": "https://assets.ngc.nvidia.com/products/api-catalog/images/google-paligemma.jpg",
    "PREVIEW": "true",
    "last_month_api_invocation_count": "4021"
  },
  "id": "google/google-paligemma",
  "description": "Vision language model adept at comprehending text and visual inputs to produce informative responses",
  "context_length": null
}

openrouter.ai/google/google-paligemma

Google: Gemini 4 Argon

GoogleGemini 4 Argon

google/gemini-4-argon

2026-10-13text+image+file+audio+video->textreasoning: high / medium / low

Intelligence index

50.4

Artificial Analysis

Design Arena

1266 Elo · #1

agenticgamedev · 51.1% wins

Input

per 1M tokens

Output

$10

per 1M tokens

Cached input

$0.10

per 1M tokens

Context

1.0M

tokens it reads

Max output

944K

tokens it writes

Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...

inspect — the catalog entry

{
  "id": "google/gemini-4-argon",
  "canonical_slug": "google/gemini-4-argon-20261013",
  "hugging_face_id": null,
  "name": "Google: Gemini 4 Argon",
  "created": 1791907477,
  "description": "Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...",
  "context_length": 1048576,
  "architecture": {
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    "input_modalities": [
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    "tokenizer": "Gemini",
    "instruct_type": null
  },
  "pricing": {
    "prompt": "0.000002",
    "completion": "0.00001",
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    "audio": "0.000002",
    "input_audio_cache": "0.0000001",
    "web_search": "0.014",
    "internal_reasoning": "0.00001",
    "input_cache_read": "0.0000001",
    "input_cache_write": "0.0000001875"
  },
  "top_provider": {
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    "max_completion_tokens": 943718,
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  "per_request_limits": null,
  "supported_parameters": [
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  "default_parameters": {
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  },
  "supported_voices": null,
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  "links": {
    "details": "/api/v1/models/google/gemini-4-argon-20261013/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
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  "benchmarks": {
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        "category": "agenticgamedev",
        "elo": 1266,
        "win_rate": 51.1,
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        "win_rate": 60.5,
        "rank": 2
      },
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    ],
    "artificial_analysis": {
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      "coding_index": null,
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  "reasoning": {
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      "low"
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    "default_effort": "medium"
  }
}

openrouter.ai/google/gemini-4-argon

Google: Gemini 4 Argon (batch)

GoogleGemini 4 Argon (batch)

google/gemini-4-argon:batch

2026-10-13text+image+file+audio+video->textreasoning: high / medium / low

Intelligence index

50.4

Artificial Analysis

Design Arena

1266 Elo · #1

agenticgamedev · 51.1% wins

Input

per 1M tokens

Output

per 1M tokens

Cached input

$0.05

per 1M tokens

Context

1.0M

tokens it reads

Max output

944K

tokens it writes

inspect — the catalog entry

{
  "id": "google/gemini-4-argon:batch",
  "canonical_slug": "google/gemini-4-argon-20261013",
  "hugging_face_id": null,
  "name": "Google: Gemini 4 Argon (batch)",
  "created": 1791907477,
  "description": "Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents. Google trained it to keep context across...",
  "context_length": 1048576,
  "architecture": {
    "modality": "text+image+file+audio+video->text",
    "input_modalities": [
      "audio",
      "file",
      "image",
      "text",
      "video"
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    "tokenizer": "Gemini",
    "instruct_type": null
  },
  "pricing": {
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    "completion": "0.000005",
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    "audio": "0.000001",
    "input_audio_cache": "0.00000005",
    "web_search": "0.014",
    "internal_reasoning": "0.000005",
    "input_cache_read": "0.00000005",
    "input_cache_write": "0.0000001875"
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    "tools",
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  "default_parameters": {
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  "links": {
    "details": "/api/v1/models/google/gemini-4-argon-20261013/endpoints"
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  "endpoints": [
    "/api/v1/batches"
  ],
  "benchmarks": {
    "design_arena": [
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        "arena": "agents",
        "category": "agenticgamedev",
        "elo": 1266,
        "win_rate": 51.1,
        "rank": 1
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        "elo": 1408,
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      },
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}

openrouter.ai/google/gemini-4-argon:batch

Google: Nano Banana 2.1

GoogleNano Banana 2.1

google/gemini-nano-banana-2.1

2026-10-06text+image->text+imagereasoning: high / minimal / none

Input

$1.50

per 1M tokens

Output

$7.50

per 1M tokens

Context

66K

tokens it reads

Max output

59K

tokens it writes

Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization,...

inspect — the catalog entry

{
  "id": "google/gemini-nano-banana-2.1",
  "canonical_slug": "google/gemini-nano-banana-2.1-20261006",
  "hugging_face_id": null,
  "name": "Google: Nano Banana 2.1",
  "created": 1791300825,
  "description": "Nano Banana 2.1 (Gemini Nano Banana 2.1) is Google's image generation and editing model on the Flash tier, succeeding Nano Banana 2 and Nano Banana Pro. It improves product recontextualization,...",
  "context_length": 65536,
  "architecture": {
    "modality": "text+image->text+image",
    "input_modalities": [
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  },
  "pricing": {
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    "completion": "0.0000075",
    "image_output": "0.00003",
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  "supported_parameters": [
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  "links": {
    "details": "/api/v1/models/google/gemini-nano-banana-2.1-20261006/endpoints"
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}

openrouter.ai/google/gemini-nano-banana-2.1

Google: Gemini 3.8 Flash

GoogleGemini 3.8 Flash

google/gemini-3.8-flash

2026-09-02text+image+file+audio+video->textreasoning: high / medium / low

Intelligence index

30.8

Artificial Analysis

Coding index

76.3

Artificial Analysis

Agentic index

40.2

Artificial Analysis

Design Arena

1236 Elo · #3

codetovideo · 58.3% wins

Input

$0.83

per 1M tokens

Output

$4.13

per 1M tokens

Cached input

$0.08

per 1M tokens

Context

1.0M

tokens it reads

Max output

66K

tokens it writes

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

inspect — the catalog entry

{
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  "hugging_face_id": null,
  "name": "Google: Gemini 3.8 Flash",
  "created": 1788362056,
  "description": "Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.",
  "context_length": 1048576,
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      {
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      "intelligence_index": 30.8,
      "coding_index": 76.3,
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}

openrouter.ai/google/gemini-3.8-flash

Google: Gemini 3.8 Flash (batch)

GoogleGemini 3.8 Flash (batch)

google/gemini-3.8-flash:batch

2026-09-02text+image+file+audio+video->textreasoning: high / medium / low

Intelligence index

30.8

Artificial Analysis

Coding index

76.3

Artificial Analysis

Agentic index

40.2

Artificial Analysis

Design Arena

1236 Elo · #3

codetovideo · 58.3% wins

Input

$0.38

per 1M tokens

Output

$1.88

per 1M tokens

Cached input

$0.04

per 1M tokens

Context

1.0M

tokens it reads

Max output

66K

tokens it writes

Gemini 3.8 Flash is Google's most intelligent Flash model with significant gains from 3.7 Flash across software engineering, agentic tasks, and multi-step reasoning.

inspect — the catalog entry

{
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        "elo": 1092,
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      {
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        "elo": 1138,
        "win_rate": 40.4,
        "rank": 21
      },
      {
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        "category": "spreadsheet",
        "elo": 1070,
        "win_rate": 42.2,
        "rank": 21
      },
      {
        "arena": "agents",
        "category": "webapps",
        "elo": 1226,
        "win_rate": 46.9,
        "rank": 15
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        "elo": 1291,
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        "elo": 1273,
        "win_rate": 51.5,
        "rank": 26
      },
      {
        "arena": "models",
        "category": "gamedev",
        "elo": 1305,
        "win_rate": 51.1,
        "rank": 17
      },
      {
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        "elo": 1293,
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        "win_rate": 53,
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}

openrouter.ai/google/gemini-3.8-flash:batch

Google: Gemini 3.7 Flash

GoogleGemini 3.7 Flash

google/gemini-3.7-flash

2026-08-13text+image+file+audio+video->textreasoning: high / medium / low

Coding index

76.1

Artificial Analysis

Agentic index

35.2

Artificial Analysis

Design Arena

1264 Elo · #6

godotgamedev · 50.6% wins

Input

$0.75

per 1M tokens

Output

$3.75

per 1M tokens

Cached input

$0.07

per 1M tokens

Context

1.0M

tokens it reads

Max output

66K

tokens it writes

Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step...

inspect — the catalog entry

{
  "id": "google/gemini-3.7-flash",
  "canonical_slug": "google/gemini-3.7-flash-20260813",
  "hugging_face_id": null,
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  "created": 1786640581,
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  "context_length": 1048576,
  "architecture": {
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    "input_modalities": [
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    "output_modalities": [
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    "tokenizer": "Gemini",
    "instruct_type": null
  },
  "pricing": {
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    "web_search": "0.014",
    "internal_reasoning": "0.00000375",
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    "input_cache_write": "0.0000000416666666666667"
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    "tool_choice",
    "tools",
    "top_p"
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  "default_parameters": {},
  "supported_voices": null,
  "knowledge_cutoff": null,
  "expiration_date": null,
  "links": {
    "details": "/api/v1/models/google/gemini-3.7-flash-20260813/endpoints"
  },
  "endpoints": [
    "/api/v1/chat/completions",
    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
  ],
  "benchmarks": {
    "design_arena": [
      {
        "arena": "agents",
        "category": "agenticgamedev",
        "elo": 1181,
        "win_rate": 52.1,
        "rank": 7
      },
      {
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        "category": "androidnative",
        "elo": 1239,
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        "elo": 1316,
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        "category": "gamedev",
        "elo": 1319,
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      {
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        "elo": 1283,
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        "elo": 1294,
        "win_rate": 51.9,
        "rank": 20
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      {
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        "category": "website",
        "elo": 1303,
        "win_rate": 53.8,
        "rank": 13
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    ],
    "artificial_analysis": {
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      "agentic_index": 35.2
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  },
  "reasoning": {
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    "supported_efforts": [
      "high",
      "medium",
      "low"
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    "default_effort": "medium"
  }
}

openrouter.ai/google/gemini-3.7-flash

Google: Gemini 3.7 Flash (batch)

GoogleGemini 3.7 Flash (batch)

google/gemini-3.7-flash:batch

2026-08-13text+image+file+audio+video->textreasoning: high / medium / low

Coding index

76.1

Artificial Analysis

Agentic index

35.2

Artificial Analysis

Design Arena

1264 Elo · #6

godotgamedev · 50.6% wins

Input

$0.38

per 1M tokens

Output

$1.88

per 1M tokens

Cached input

$0.04

per 1M tokens

Context

1.0M

tokens it reads

Max output

66K

tokens it writes

inspect — the catalog entry

{
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  "canonical_slug": "google/gemini-3.7-flash-20260813",
  "hugging_face_id": null,
  "name": "Google: Gemini 3.7 Flash (batch)",
  "created": 1786640581,
  "description": "Gemini 3.7 Flash is a multimodal model from Google for fast agentic workflows, coding, and complex multi-step reasoning. It is designed for tasks that require responsive performance and reliable multi-step...",
  "context_length": 1048576,
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    "input_modalities": [
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  "benchmarks": {
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      {
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        "category": "agenticgamedev",
        "elo": 1181,
        "win_rate": 52.1,
        "rank": 7
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        "elo": 1316,
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        "elo": 1319,
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      {
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        "elo": 1283,
        "win_rate": 53.9,
        "rank": 11
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        "category": "uicomponent",
        "elo": 1294,
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      {
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        "elo": 1303,
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    ],
    "artificial_analysis": {
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  },
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  }
}

openrouter.ai/google/gemini-3.7-flash:batch

Google: Gemini 3.6 Flash

GoogleGemini 3.6 Flash

google/gemini-3.6-flash

2026-07-21text+image+file+audio+video->textreasoning: high / medium / low / minimal

Coding index

69.2

Artificial Analysis

Agentic index

Artificial Analysis

Design Arena

1274 Elo · #10

asciiart · 56.7% wins

Input

$0.75

per 1M tokens

Output

$3.75

per 1M tokens

Cached input

$0.07

per 1M tokens

Context

1.0M

tokens it reads

Max output

66K

tokens it writes

Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and...

inspect — the catalog entry

{
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  "canonical_slug": "google/gemini-3.6-flash-20260721",
  "hugging_face_id": null,
  "name": "Google: Gemini 3.6 Flash",
  "created": 1784646733,
  "description": "Gemini 3.6 Flash is a high-efficiency model from Google for coding, agentic workflows, and web and app development. It is designed to produce polished outputs with fewer unnecessary edits and...",
  "context_length": 1048576,
  "architecture": {
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  "links": {
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    "/api/v1/completions",
    "/api/v1/messages",
    "/api/v1/responses"
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  "benchmarks": {
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      },
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openrouter.ai/google/gemini-3.6-flash

the whole object this page is drawn from, as JSON · Open JSON

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