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2,816 models1,617 with prices34 metricsUpdated Oct 18, 2026 ↗

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googleListed Apr 3

Google: Gemma 4 26B A4B (free)

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

262.1K context26BImage inputVideo inputNo reported score
No reported score
$0.00in$0.00out/ 1M tokens · USDGoogle AI Studio · via OpenRouter · 2 endpointsgoogle-ai-studio
googleListed Apr 2

Google: Gemma 4 31B (free)

Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native…

262.1K context31BImage inputVideo inputNo reported score
No reported score
$0.00in$0.00out/ 1M tokens · USDGoogle AI Studio · via OpenRouter · 2 endpointsgoogle-ai-studio
rekaaiListed Mar 20

Reka Edge

Reka Edge is an extremely efficient 7B multimodal vision-language model that accepts image/video+text inputs and generates text outputs. This model is optimized specifically to deliver industry-leading…

16.4K contextImage inputVideo inputNo reported score
No reported score
$0.10in$0.10out/ 1M tokens · USDReka · via OpenRouter · 2 endpointsreka
mistralaiListed Mar 16

Mistral: Mistral Small 4

Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...

262.1K contextImage inputTool callingNo reported score
No reported score
$0.15in$0.60out/ 1M tokens · USDMistral · via OpenRouter · 5 endpointsmistral/zdr
mistralaiListed Mar 16

Mistral: Mistral Small 4 (batch)

Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...

262.1K contextImage inputTool callingNo reported score
No reported score
$0.075in$0.30out/ 1M tokens · USDMistral · via OpenRouter · 2 endpointsmistral
googleListed Mar 11

Google: Gemma 4 26B A4B

Gemma 4 26B A4B IT is an instruction-tuned Mixture-of-Experts (MoE) model from Google DeepMind. Despite 25.2B total parameters, only 3.8B activate per token during inference — delivering near-31B quality at...

262.1K context26BImage inputVideo inputNo reported score
No reported score
$0.042in$0.22out/ 1M tokens · USDDarkbloom · via OpenRouter · 19 endpointsdarkbloom
QwenListed Feb 27

Qwen3.5-9B

Qwen3.5-9B is a high-performance model from Alibaba's Qwen3.5 series with a hybrid Gated Delta Networks and sparse MoE architecture. It features a 262K token context window, thinking/reasoning mode, tool…

262.1K context9BImage inputVideo inputNo reported score
No reported score
$0.08in$0.13out/ 1M tokens · USDDarkbloom · via OpenRouter · 12 endpointsdarkbloom/fp4 · quantization=fp4
nvidiaListed Feb 25

NVIDIA: Llama Nemotron Embed VL 1B V2 (free)

The Llama Nemotron Embed VL 1B V2 embedding model is optimized for multimodal question-answering retrieval. The model can embed 'documents' in the form of image, text, or image and text...

131.1K context1BImage inputOpen weightsNo reported score
No reported score
$0.00in$0.00out/ 1M tokens · USDOpenRouter
qwenListed Feb 24

Qwen: Qwen3.5-122B-A10B

The Qwen3.5 122B-A10B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference…

262.1K context122BImage inputVideo inputNo reported score
No reported score
$0.26in$2.08out/ 1M tokens · USDAlibaba · via OpenRouter · 7 endpointsalibaba
QwenListed Feb 24

Qwen3.5-27B

Qwen3.5-27B is Alibaba's largest dense Qwen3.5 model, delivering near-frontier quality across reasoning, coding, and instruction following. It features a 262K token context window (extensible to 1M),…

262.1K context27BImage inputVideo inputNo reported score
No reported score
$0.195in$1.56out/ 1M tokens · USDAlibaba · via OpenRouter · 12 endpointsalibaba
QwenListed Feb 24

Qwen3.5-35B-A3B

Qwen3.5-35B-A3B is an efficient Mixture-of-Experts model from Alibaba's Qwen3.5 series with 35B total parameters and only 3B activated per token. It features a 262K token context window (extensible to 1M…

262.1K context35BImage inputVideo inputNo reported score
No reported score
$0.065in$0.75out/ 1M tokens · USDDarkbloom · via OpenRouter · 11 endpointsdarkbloom/fp4 · quantization=fp4
QwenListed Feb 16

Qwen3.5-397B-A17B

Qwen3.5-397B-A17B is Alibaba's most capable Qwen3.5 model, a Mixture-of-Experts architecture with 397B total parameters and 17B activated per token. It features a 262K token context window (extensible to 1M…

262.1K context397BImage inputVideo inputNo reported score
No reported score
$0.39in$2.34out/ 1M tokens · USDAlibaba · via OpenRouter · 17 endpointsalibaba
black-forest-labsListed Jan 14

Black Forest Labs: FLUX.2 Klein 4B

FLUX.2 [klein] 4B is the fastest and most cost-effective model in the FLUX.2 family, optimized for high-throughput use cases while maintaining excellent image quality. Pricing is based on the output...

41K context4BImage inputOpen weightsNo reported score
No reported score
Price not listed
moonshotaiListed Jan 1

MoonshotAI: Kimi K2.5

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over…

262.1K contextImage inputTool callingNo reported score
No reported score
$0.45in$2.25out/ 1M tokens · USDdeepinfra · via Hugging Face · 10 endpoints
zai-orgListed Dec 7

GLM-4.6V-FP8

Image inputOpen weightsNo reported score
No reported score
Price not listed
z-aiListed Dec 7

Z.ai: GLM 4.6V

GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex…

131.1K contextImage inputVideo inputNo reported score
No reported score
$0.30in$0.90out/ 1M tokens · USDExperiential · 5 endpointsStandard list rate
zai-orgListed Dec 7

GLM-4.6V-Flash

131.1K contextImage inputOpen weightsNo reported score
No reported score
$0.30in$0.90out/ 1M tokens · USDnovita · via Hugging Face · 2 endpoints
mistralaiListed Dec 2

Mistral: Ministral 3 14B 2512

The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language...

262.1K context14BImage inputTool callingNo reported score
No reported score
$0.20in$0.20out/ 1M tokens · USDMistral · via OpenRouter · 4 endpointsmistral/zdr
mistralaiListed Dec 2

Mistral: Ministral 3 8B 2512

A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.

262.1K context8BImage inputTool callingNo reported score
No reported score
$0.15in$0.15out/ 1M tokens · USDMistral · via OpenRouter · 4 endpointsmistral/zdr
mistralaiListed Dec 2

Mistral: Ministral 3 8B 2512 (batch)

A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.

262.1K context8BImage inputTool callingNo reported score
No reported score
$0.075in$0.075out/ 1M tokens · USDMistral · via OpenRouter · 2 endpointsmistral
mistralaiListed Dec 2

Mistral: Ministral 3 3B 2512

The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.

131.1K context3BImage inputTool callingNo reported score
No reported score
$0.10in$0.10out/ 1M tokens · USDMistral · via OpenRouter · 4 endpointsmistral/zdr
qwenListed Oct 14

Qwen: Qwen3 VL 8B Instruct

Qwen3-VL-8B-Instruct is a multimodal vision-language model from the Qwen3-VL series, built for high-fidelity understanding and reasoning across text, images, and video. It features improved multimodal…

262.1K context8BImage inputTool callingNo reported score
No reported score
$0.25in$0.75out/ 1M tokens · USDParasail · via OpenRouter · 2 endpointsparasail/bf16 · quantization=bf16