The LLM Price Index
Every major large language model, normalized to dollars per million tokens. Scored on value, cheapness, and frontier capability. Independent, automated, refreshed daily.
What this is
The LLM Price Index is a live, independently maintained price comparison for every large language model offered through the OpenRouter catalog. Input and output pricing is normalized to dollars per million tokens, blended 3:1 to produce a single comparable figure, and scored 0–10 on three axes: value, cheapness, and frontier capability. The cheapest paid model right now is Ling-2.6-flash at $0.015 per million tokens (3:1 blended).
Grok 4.20
7.4/10Grok 4.20 is a reasoning model from xAI with industry-leading speed and agentic tool calling capabilities. It combines the lowest hallucination rate…
Grok 4.3
7.4/10Grok 4.3 is a reasoning model from xAI. It accepts text and image inputs with text output, and is suited for agentic…
GLM 4.7 Flash
7.4/10As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding…
Ministral 3 8B 2512
7.4/10A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities.
Ministral 3 3B 2512
7.4/10The smallest model in the Ministral 3 family, Ministral 3 3B is a powerful, efficient tiny language model with vision capabilities.
Seed-2.0-Mini
7.3/10Seed-2.0-mini targets latency-sensitive, high-concurrency, and cost-sensitive scenarios, emphasizing fast response and flexible inference deployment. It delivers performance comparable to ByteDance-Seed-1.6, supports 256k…
Gemini 2.5 Flash Lite Preview 09-2025
7.3/10Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers…
Gemini 2.5 Flash Lite
7.3/10Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers…
Ministral 3 14B 2512
7.3/10The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small…
Step 3.5 Flash
7.3/10Step 3.5 Flash is StepFun's most capable open-source foundation model. Built on a sparse Mixture of Experts (MoE) architecture, it selectively activates…
Gemini 3 Flash Preview
7.3/10Gemini 3 Flash Preview is a high speed, high value thinking model designed for agentic workflows, multi turn chat, and coding assistance.…
Gemini 3.1 Flash Lite Preview
7.3/10Gemini 3.1 Flash Lite Preview is Google's high-efficiency model optimized for high-volume use cases. It outperforms Gemini 2.5 Flash Lite on overall…
Qwen3 235B A22B Instruct 2507
7.3/10Qwen3-235B-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…
Qwen3.5 Plus 2026-02-15
7.3/10The Qwen3.5 native vision-language series Plus models are built on a hybrid architecture that integrates linear attention mechanisms with sparse mixture-of-experts models,…
Granite 4.0 Micro
7.3/10Granite-4.0-H-Micro is a 3B parameter from the Granite 4 family of models. These models are the latest in a series of models…
gpt-oss-20b
7.2/10gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with…
Mistral Small 4
7.2/10Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into…
MiMo-V2-Flash
7.2/10MiMo-V2-Flash is an open-source foundation language model developed by Xiaomi. It is a Mixture-of-Experts model with 309B total parameters and 15B active…
Mistral Nemo
7.2/10A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting…
Gemini 3.5 Flash
7.2/10Gemini 3.5 Flash is Google's high-efficiency multimodal model, bringing near-Pro level coding and reasoning at Flash-tier cost and speed. It is highly…
Ring-2.6-1T
7.2/10Ring-2.6-1T is a 1T-parameter-scale thinking model with 63B active parameters, built for real-world agent workflows that require both strong capability and operational…
Nemotron Nano 9B V2
7.2/10NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and…
gpt-oss-120b
7.1/10gpt-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…
Llama 3.1 8B Instruct
7.1/10Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and…
Qwen3.5-35B-A3B
7.1/10The Qwen3.5 Series 35B-A3B is a native vision-language model designed with a hybrid architecture that integrates linear attention mechanisms and a sparse…
Gemini 2.0 Flash Lite
7.1/10Gemini 2.0 Flash Lite offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on…
Llama 4 Scout
7.1/10Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a…
GPT-5 Nano
7.1/10GPT-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…
Qwen Plus 0728 (thinking)
7.1/10Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed,…
Qwen Plus 0728
7.1/10Qwen Plus 0728, based on the Qwen3 foundation model, is a 1 million context hybrid reasoning model with a balanced performance, speed,…
Qwen3 30B A3B Instruct 2507
7.1/10Qwen3-30B-A3B-Instruct-2507 is a 30.5B-parameter mixture-of-experts language model from Qwen, with 3.3B active parameters per inference. It operates in non-thinking mode and is…
Qwen3.7 Max
7.1/10Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series. It supports text input and output and is designed for agent-centric workloads, with…
Mistral Small 3.2 24B
7.0/10Mistral-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…
GPT-4.1 Nano
7.0/10For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance…
Gemini 2.0 Flash
7.0/10Gemini Flash 2.0 offers a significantly faster time to first token (TTFT) compared to [Gemini Flash 1.5](/google/gemini-flash-1.5), while maintaining quality on par…
Qwen3 VL 32B Instruct
7.0/10Qwen3-VL-32B-Instruct is a large-scale multimodal vision-language model designed for high-precision understanding and reasoning across text, images, and video. With 32 billion parameters,…
Qwen3 VL 8B Instruct
7.0/10Qwen3-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…
Qwen3 Coder 30B A3B Instruct
7.0/10Qwen3-Coder-30B-A3B-Instruct is a 30.5B parameter Mixture-of-Experts (MoE) model with 128 experts (8 active per forward pass), designed for advanced code generation, repository-scale…
Nova 2 Lite
7.0/10Nova 2 Lite is a fast, cost-effective reasoning model for everyday workloads that can process text, images, and videos to generate text.…
Gemma 3 4B
7.0/10Gemma 3 introduces multimodality, supporting vision-language input and text outputs. It handles context windows up to 128k tokens, understands over 140 languages,…
LFM2-24B-A2B
7.0/10LFM2-24B-A2B is the largest model in the LFM2 family of hybrid architectures designed for efficient on-device deployment. Built as a 24B parameter…
Qwen3 VL 30B A3B Instruct
7.0/10Qwen3-VL-30B-A3B-Instruct is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Instruct variant optimizes instruction-following…
Grok Build 0.1
7.0/10Grok Build 0.1 is xAI’s fast coding model trained specifically for agentic software engineering workflows. It supports text and image inputs with…
Qwen2.5 7B Instruct
6.9/10Qwen2.5 7B is the latest series of Qwen large language models. Qwen2.5 brings the following improvements upon Qwen2: - Significantly more knowledge…
Qwen3 Coder Flash
6.9/10Qwen3 Coder Flash is Alibaba's fast and cost efficient version of their proprietary Qwen3 Coder Plus. It is a powerful coding agent…
Llama 4 Maverick
6.9/10Llama 4 Maverick 17B Instruct (128E) is a high-capacity multimodal language model from Meta, built on a mixture-of-experts (MoE) architecture with 128…
Reka Edge
6.9/10Reka Edge is an extremely efficient 7B multimodal vision-language model that accepts image/video+text inputs and generates text outputs. This model is optimized…
Nova Micro 1.0
6.9/10Amazon Nova Micro 1.0 is a text-only model that delivers the lowest latency responses in the Amazon Nova family of models at…
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Price drops, new models, deprecations
Every Tuesday: which models got cheaper, which launched, which got pulled. Five minutes. No filler.
Three axes, one overall score
- Value (35%) — capability per dollar. Context length, vision, tools, and structured-output support divided by log-scaled blended price.
- Cheapness (35%) — raw affordability. Free models score 10. Paid models use an inverse log curve anchored at $0.01 / Mtok.
- Frontier (30%) — how close to the state of the art. Recent releases, long context windows, and premium pricing all contribute.
Blended price formula
- Most production workloads are input-heavy, so the index uses a 3:1 blended price:
(input × 0.75) + (output × 0.25). - All prices are normalized to dollars per million tokens. OpenRouter publishes per-token figures which we multiply by 1,000,000 before display.
Where does the pricing data come from?
Every model and price on this page is sourced from OpenRouter's public models API, which aggregates pricing directly from model providers including Anthropic, OpenAI, Google, Mistral, Meta, xAI, DeepSeek, and dozens of others. The pipeline re-fetches and re-scores the entire catalog once per day.
Why normalize to $/million tokens?
Model providers publish prices in inconsistent units — per 1K tokens, per million tokens, per character, sometimes per request. Comparing them directly is error-prone. Dollars per million tokens is the industry's most common reporting unit and makes cross-provider comparisons immediate and honest.
What does "3:1 blended" mean?
Most production LLM workloads are input-heavy — context, RAG retrievals, system prompts — while output is comparatively short. A 3:1 input:output ratio is the informal industry convention for producing a single number that reflects typical cost: (input × 0.75) + (output × 0.25). Your actual ratio may differ; always check both input and output columns for workloads with long generations.
What's the cheapest LLM right now?
The cheapest paid model as of the latest scan is Ling-2.6-flash from Inclusionai at $0.015 per million tokens (3:1 blended). Sort by "Cheapest" above for the full ranking. Many providers also offer free-tier variants of their models, which score a perfect 10 on the cheapness axis.
Is this affiliated with OpenRouter or any provider?
No. MegaOne AI is independent. OpenRouter is used as a public data source because their models API is the most complete and up-to-date LLM catalog available, but this directory is not operated by OpenRouter and we rate all models — including ones that compete with one another.
How often does the price index update?
A full re-fetch, re-score, and daily snapshot runs once per 24 hours. Snapshots are written to a history table so we can build price-over-time charts and detect drops. New models typically appear within 24 hours of being added to OpenRouter.
Is it free to use?
Yes. Browsing, filtering, sorting, and searching the entire price index is free. The weekly email briefing is free. There is no account required and no paywall.