openai/gpt-5-nano
Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs
- Context
- 400K
- Input
- $0.05/M
- Output
- $0.4/M
Filter 123 source-linked models by creator, price, context, modality, and published benchmark coverage.
openai/gpt-5-nano
Tiny GPT-5 lane for routing, extraction, classification, and bulk jobs
openai/gpt-5-nano:batch
GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...
mistralai/ministral-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...
openai/o3
Deliberate o-series reasoner for hard math, coding, and multi-step analysis
google/gemini-3.1-flash-lite-preview
Low-latency Gemini model for high-volume multimodal and agent workloads
mistralai/mistral-medium-3
Mistral Medium 3 is a high-performance enterprise-grade language model designed to deliver frontier-level capabilities at significantly reduced operational cost. It balances state-of-the-art reasoning and multimodal performance with 8× lower cost...
openai/o4-mini
Fast o-series model for compact reasoning, coding, and tool use
openai/gpt-oss-120b:free
gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized...
openai/gpt-oss-120b
Open GPT reasoning model for self-hosted agents and controllable deployments
mistralai/ministral-8b-2512
A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
inception/mercury-2
Mercury 2 is an extremely fast reasoning LLM, and the first reasoning diffusion LLM (dLLM). Instead of generating tokens sequentially, Mercury 2 produces and refines multiple tokens in parallel, achieving...
moonshotai/kimi-k2
Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for...
openai/gpt-4.1-nano
Tiny GPT-4.1 option for classification, routing, and very high-volume tasks
mistralai/codestral-2508
Mistral's cutting-edge language model for coding released end of July 2025. Codestral specializes in low-latency, high-frequency tasks such as fill-in-the-middle (FIM), code correction and test generation. [Blog Post](https://mistral.ai/news/codestral-25-08)
qwen/qwen3-235b-a22b-thinking-2507
Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...
qwen/qwen3-235b-a22b-2507
Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...
mistralai/ministral-3b-2512
The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
qwen/qwen3-235b-a22b
Qwen3-235B-A22B is a 235B parameter mixture-of-experts (MoE) model developed by Qwen, activating 22B parameters per forward pass. It supports seamless switching between a "thinking" mode for complex reasoning, math, and...
openai/gpt-4o
Omni-era GPT for multimodal chat, practical coding, and general assistants
qwen/qwen3-30b-a3b
Qwen3, the latest generation in the Qwen large language model series, features both dense and mixture-of-experts (MoE) architectures to excel in reasoning, multilingual support, and advanced agent tasks. Its unique...
mistralai/mistral-small-3.2-24b-instruct
Mistral-Small-3.2-24B-Instruct-2506 is an updated 24B parameter model from Mistral optimized for instruction following, repetition reduction, and improved function calling. Compared to the 3.1 release, version 3.2 significantly improves accuracy on...
meta-llama/llama-4-maverick
Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128 experts and 17 billion active parameters per forward...
meta-llama/llama-4-scout
Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...
| Model | Creator | Raw benchmark score | Input types | Context | Input / Output | Released | Compare |
|---|---|---|---|---|---|---|---|
| GPT-5 Nanoopenai/gpt-5-nano | 1102.0 | 400K | $0.05 / $0.4 | 2025-08-07 | |||
| OpenAI: GPT-5 Nano (batch)openai/gpt-5-nano:batch | 1102.0 | 400K | $0.025 / $0.2 | Undated | |||
| Mistral: Ministral 3 14B 2512mistralai/ministral-14b-2512 | 1094.0 | 262.144K | $0.2 / $0.2 | Undated | |||
| o3openai/o3 | 1090.0 | 200K | $2 / $8 | 2025-04-16 | |||
| Gemini 3.1 Flash Lite Previewgoogle/gemini-3.1-flash-lite-preview | 1085.0 | 1.04858M | $0.25 / $1.5 | 2026-03-03 | |||
| Mistral: Mistral Medium 3mistralai/mistral-medium-3 | 1074.0 | 131.072K | $0.4 / $2 | Undated | |||
| o4-miniopenai/o4-mini | 1059.0 | 200K | $1.1 / $4.4 | 2025-04-16 | |||
| OpenAI: gpt-oss-120b (free)openai/gpt-oss-120b:free | 1054.0 | 131.072K | Free / Free | Undated | |||
| GPT OSS 120Bopenai/gpt-oss-120b | 1049.0 | 131.072K | $0.03 / $0.17 | 2025-08-05 | |||
| Mistral: Ministral 3 8B 2512mistralai/ministral-8b-2512 | 1047.0 | 262.144K | $0.15 / $0.15 | Undated | |||
| Inception: Mercury 2inception/mercury-2 | 1032.0 | 128K | $0.25 / $0.75 | Undated | |||
| MoonshotAI: Kimi K2 0711moonshotai/kimi-k2 | 1030.0 | 131.072K | $0.57 / $2.3 | Undated | |||
| GPT-4.1 nanoopenai/gpt-4.1-nano | 1027.0 | 1.04758M | $0.1 / $0.4 | 2025-04-14 | |||
| Mistral: Codestral 2508mistralai/codestral-2508 | 1023.0 | 256K | $0.3 / $0.9 | Undated | |||
| Qwen: Qwen3 235B A22B Thinking 2507qwen/qwen3-235b-a22b-thinking-2507 | 1014.0 | 131.072K | $0.23 / $2.3 | Undated | |||
| Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 1008.0 | 262.144K | $0.09 / $0.55 | Undated | |||
| Mistral: Ministral 3 3B 2512mistralai/ministral-3b-2512 | 1005.0 | 131.072K | $0.1 / $0.1 | Undated | |||
| Qwen: Qwen3 235B A22Bqwen/qwen3-235b-a22b | 985.0 | 131.072K | $0.455 / $1.82 | Undated | |||
| GPT-4oopenai/gpt-4o | 962.0 | 128K | $2.5 / $10 | 2024-05-13 | |||
| Qwen: Qwen3 30B A3Bqwen/qwen3-30b-a3b | 954.0 | 40.96K | $0.12 / $0.5 | Undated | |||
| Mistral: Mistral Small 3.2 24Bmistralai/mistral-small-3.2-24b-instruct | 945.0 | 131.072K | $0.1 / $0.3 | Undated | |||
| Meta: Llama 4 Maverickmeta-llama/llama-4-maverick | 894.0 | 1.04858M | $0.2 / $0.8 | Undated | |||
| Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 829.0 | 327.68K | $0.1 / $0.3 | Undated |