ZERNO · Модели
Сколько стоит миллион токенов
Цена первоисточника, пересчитанная в рубли по курсу ЦБ. Мы не прячем, откуда берём цифры, и не показываем те, которых у нас пока нет.
Сверяем цены с курсом ЦБ…
Собираем каталог: цены и курс на сегодня…
Цена первоисточника, пересчитанная в рубли по курсу ЦБ. Мы не прячем, откуда берём цифры, и не показываем те, которых у нас пока нет.
Сверяем цены с курсом ЦБ…
Собираем каталог: цены и курс на сегодня…
Источник цен — краулер ZERNO: openrouter.ai и российские перепродавцы, снято 2026-08-20. Курс 85.16 ₽ за доллар на 19.08.2026, по данным ЦБ. Наценки в этих ценах нет: доступ к моделям мы ещё не продаём.
| Модель | Вход, ₽ / 1M | Выход, ₽ / 1M | Дешевле всего у | Контекст |
|---|---|---|---|---|
Perplexity: Embed V1 0.6Bperplexity/pplx-embed-v1-0.6b | 0.341 | 0 | — | 32 000 |
BAAI: bge-base-en-v1.5baai/bge-base-en-v1.5 | 0.426 | 0 | — | 512 |
Intfloat: E5-Base-v2intfloat/e5-base-v2 | 0.426 | 0 | — | 512 |
Sentence Transformers: all-MiniLM-L12-v2sentence-transformers/all-minilm-l12-v2 | 0.426 | 0 | — | 512 |
Sentence Transformers: all-MiniLM-L6-v2sentence-transformers/all-minilm-l6-v2 | 0.426 | 0 | — | 512 |
Sentence Transformers: all-mpnet-base-v2sentence-transformers/all-mpnet-base-v2 | 0.426 | 0 | — | 512 |
Sentence Transformers: multi-qa-mpnet-base-dot-v1sentence-transformers/multi-qa-mpnet-base-dot-v1 | 0.426 | 0 | — | 512 |
Sentence Transformers: paraphrase-MiniLM-L6-v2sentence-transformers/paraphrase-minilm-l6-v2 | 0.426 | 0 | — | 512 |
Thenlper: GTE-Basethenlper/gte-base | 0.426 | 0 | — | 512 |
BAAI: bge-large-en-v1.5baai/bge-large-en-v1.5 | 0.852 | 0 | — | 512 |
BAAI: bge-m3baai/bge-m3 | 0.852 | 0 | — | 8 194 |
inclusionAI: Ling-2.6-flashinclusionai/ling-2.6-flash | 0.852 | 2.55 | — | 262 144 |
Intfloat: E5-Large-v2intfloat/e5-large-v2 | 0.852 | 0 | — | 512 |
Intfloat: Multilingual-E5-Largeintfloat/multilingual-e5-large | 0.852 | 0 | — | 512 |
Qwen: Qwen3 Embedding 8Bqwen/qwen3-embedding-8b | 0.852 | 0 | — | 32 768 |
Thenlper: GTE-Largethenlper/gte-large | 0.852 | 0 | — | 512 |
IBM: Granite 4.0 Microibm-granite/granite-4.0-h-micro | 1.45 | 9.54 | — | 131 000 |
Mistral: Mistral Nemomistralai/mistral-nemo | 1.62 | 2.55 | 3.83AITunnel | 131 072 |
OpenAI: Text Embedding 3 Smallopenai/text-embedding-3-small | 1.70 | 0 | — | 8 192 |
Qwen: Qwen3 Embedding 4Bqwen/qwen3-embedding-4b | 1.70 | 0 | — | 32 768 |
VoyageAI by MongoDB: voyage-4-litevoyageai/voyage-4-lite | 1.70 | 0 | — | 32 000 |
Ling-3.0-flashinclusionai/ling-3.0-flash | 1.79 | 5.37 | — | 262 144 |
Nex AGI: Nex-N2-Mininex-agi/nex-n2-mini | 2.13 | 8.52 | — | 262 144 |
OpenAI: GPT-5 Nano (batch)openai/gpt-5-nano:batch | 2.13 | 17.03 | 4.08BotHub | 400 000 |
Meta: Llama 3.2 1B Instructmeta-llama/llama-3.2-1b-instruct | 2.30 | 17.12 | 5.44AITunnel | 60 000 |
OpenAI: gpt-oss-120bopenai/gpt-oss-120b | 2.55 | 14.48 | 4.86BotHub | 131 072 |
OpenAI: gpt-oss-20bopenai/gpt-oss-20b | 2.55 | 11.07 | 4.86BotHub | 131 072 |
Perplexity: Embed V1 4Bperplexity/pplx-embed-v1-4b | 2.55 | 0 | — | 32 000 |
Qwen: Qwen3.7 Flashqwen/qwen3.7-flash | 2.55 | 11.07 | 6.04AITunnel | 1 000 000 |
Upstage: Solar Pro 4upstage/solar-pro4 | 2.55 | 10.22 | — | 524 288 |
Amazon: Nova Micro 1.0amazon/nova-micro-v1 | 2.98 | 11.92 | 48.35VseGPT | 128 000 |
Cohere: Command R7B (12-2024)cohere/command-r7b-12-2024 | 3.19 | 12.77 | 40.29VseGPT | 128 000 |
Sao10K: Llama 3 8B Lunarissao10k/l3-lunaris-8b | 3.41 | 4.26 | — | 8 192 |
Qwen: Qwen3 30B A3B Instruct 2507qwen/qwen3-30b-a3b-instruct-2507 | 4.10 | 16.44 | 121VseGPT | 262 144 |
Google: Gemini 2.5 Flash Lite (batch)google/gemini-2.5-flash-lite:batch | 4.26 | 17.03 | 8.16BotHub | 1 048 576 |
Google: Gemma 3 12Bgoogle/gemma-3-12b-it | 4.26 | 12.77 | 8.16BotHub | 131 072 |
Google: Gemma 3 4Bgoogle/gemma-3-4b-it | 4.26 | 8.52 | 8.16BotHub | 131 072 |
IBM: Granite 4.1 8Bibm-granite/granite-4.1-8b | 4.26 | 8.52 | — | 131 072 |
Meta: Llama 3.1 8B Instructmeta-llama/llama-3.1-8b-instruct | 4.26 | 6.81 | 109VseGPT | 131 072 |
Meta: Llama 3.2 3B Instructmeta-llama/llama-3.2-3b-instruct | 4.26 | 28.10 | 10.07AITunnel | 131 072 |
Mistral: Mistral Small 3mistralai/mistral-small-24b-instruct-2501 | 4.26 | 6.81 | — | 32 768 |
NVIDIA: Nemotron 3 Nano 30B A3Bnvidia/nemotron-3-nano-30b-a3b | 4.26 | 17.03 | — | 262 144 |
OpenAI: GPT-4.1 Nano (batch)openai/gpt-4.1-nano:batch | 4.26 | 17.03 | 8.16BotHub | 1 047 576 |
OpenAI: GPT-5 Nanoopenai/gpt-5-nano | 4.26 | 34.07 | 10.07AITunnel | 400 000 |
OpenAI: Text Embedding Ada 002 (batch)openai/text-embedding-ada-002:batch | 4.26 | 0 | — | 8 192 |
Amazon: Nova Lite 1.0amazon/nova-lite-v1 | 5.11 | 20.44 | 80.59VseGPT | 300 000 |
Google: Gemma 3n 4Bgoogle/gemma-3n-e4b-it | 5.11 | 10.22 | 9.72BotHub | 32 768 |
MythoMax 13Bgryphe/mythomax-l2-13b | 5.11 | 5.11 | 161VseGPT | 8 192 |
Poolside: Laguna XS 2.1poolside/laguna-xs-2.1 | 5.11 | 10.22 | — | 262 144 |
VoyageAI by MongoDB: voyage-4voyageai/voyage-4 | 5.11 | 0 | — | 32 000 |
Z.ai: GLM 4.7 Flashz-ai/glm-4.7-flash | 5.11 | 34.07 | 12.09AITunnel | 202 752 |
OpenAI: Text Embedding 3 Large (batch)openai/text-embedding-3-large:batch | 5.54 | 0 | — | 8 192 |
Qwen: Qwen3.5-Flashqwen/qwen3.5-flash-02-23 | 5.54 | 22.14 | 13.10AITunnel | 1 000 000 |
DeepSeek V4 Flash Latest~deepseek/deepseek-v4-flash-latest | 5.54 | 11.92 | — | 1 310 720 |
Google: Gemma 4 26B A4B google/gemma-4-26b-a4b-it | 5.96 | 28.96 | 11.42BotHub | 262 144 |
Microsoft: Phi 4microsoft/phi-4 | 5.96 | 11.92 | — | 16 384 |
Qwen: Qwen3 Coder 30B A3B Instructqwen/qwen3-coder-30b-a3b-instruct | 5.96 | 23.85 | 14.00AITunnel | 262 144 |
ByteDance Seed: Seed 1.6 Flashbytedance-seed/seed-1.6-flash | 6.39 | 25.55 | — | 262 144 |
inclusionAI: Ling-2.6-1Tinclusionai/ling-2.6-1t | 6.39 | 53.23 | — | 262 144 |
inclusionAI: Ring-2.6-1Tinclusionai/ring-2.6-1t | 6.39 | 53.23 | — | 262 144 |
OpenAI: GPT-4o-mini (batch)openai/gpt-4o-mini:batch | 6.39 | 25.55 | 12.24BotHub | 128 000 |
OpenAI: gpt-oss-safeguard-20bopenai/gpt-oss-safeguard-20b | 6.39 | 25.55 | 12.24BotHub | 131 072 |
Google: Gemma 3 27Bgoogle/gemma-3-27b-it | 6.81 | 38.32 | 12.96BotHub | 262 144 |
NVIDIA: Nemotron 3.5 Lightningnvidia/nemotron-3.5-lightning | 6.81 | 17.03 | — | 1 000 000 |
Qwen: Qwen3 32Bqwen/qwen3-32b | 6.81 | 23.85 | 60.44VseGPT | 131 072 |
NVIDIA: Nemotron 3 Supernvidia/nemotron-3-super-120b-a12b | 7.24 | 34.07 | — | 1 000 000 |
DeepSeek: DeepSeek V4 Flash 0423deepseek/deepseek-v4-flash | 7.55 | 15.09 | 18.13AITunnel | 1 048 576 |
Google: Gemma 4 31Bgoogle/gemma-4-31b-it | 7.66 | 28.96 | 14.58BotHub | 262 144 |
Poolside: Laguna S 2.1poolside/laguna-s-2.1 | 7.66 | 15.33 | — | 1 048 576 |
Qwen: Qwen3 235B A22B Instruct 2507qwen/qwen3-235b-a22b-2507 | 7.66 | 46.84 | 18.00AITunnel | 262 144 |
Qwen: Qwen3 Next 80B A3B Instructqwen/qwen3-next-80b-a3b-instruct | 7.66 | 93.68 | — | 262 144 |
Mistral: Mistral Small 3.2 24Bmistralai/mistral-small-3.2-24b-instruct | 7.98 | 21.29 | 15.11AITunnel | 256 000 |
ByteDance Seed: Seed-2.0-Minibytedance-seed/seed-2.0-mini | 8.52 | 34.07 | — | 262 144 |
ByteDance: UI-TARS 7B bytedance/ui-tars-1.5-7b | 8.52 | 17.03 | — | 128 000 |
Google: Gemini 2.5 Flash Litegoogle/gemini-2.5-flash-lite | 8.52 | 34.07 | 16.32BotHub | 1 048 576 |
Meta: Llama 3.3 70B Instructmeta-llama/llama-3.3-70b-instruct | 8.52 | 27.25 | 20.15AITunnel | 131 072 |
Meta: Llama 4 Scoutmeta-llama/llama-4-scout | 8.52 | 25.55 | 20.15AITunnel | 1 310 720 |
Mistral: Ministral 3 3B 2512mistralai/ministral-3b-2512 | 8.52 | 8.52 | — | 131 072 |
Mistral: Mistral Embed 2312mistralai/mistral-embed-2312 | 8.52 | 0 | — | 8 192 |
Mistral: Voxtral Small 24B 2507mistralai/voxtral-small-24b-2507 | 8.52 | 25.55 | — | 32 000 |
OpenAI: GPT-4.1 Nanoopenai/gpt-4.1-nano | 8.52 | 34.07 | 16.32BotHub | 1 047 576 |
OpenAI: GPT-5.4 Nano (batch)openai/gpt-5.4-nano:batch | 8.52 | 53.23 | 16.20BotHub | 400 000 |
OpenAI: GPT-5.6 Luna Pro (batch)openai/gpt-5.6-luna-pro:batch | 8.52 | 51.10 | 16.32BotHub | 1 050 000 |
OpenAI: GPT-5.6 Luna (batch)openai/gpt-5.6-luna:batch | 8.52 | 51.10 | 16.32BotHub | 1 050 000 |
OpenAI: Text Embedding Ada 002openai/text-embedding-ada-002 | 8.52 | 0 | — | 8 192 |
Qwen: Qwen2.5 7B Instructqwen/qwen-2.5-7b-instruct | 8.52 | 17.03 | — | 32 768 |
Qwen: Qwen3.5-9Bqwen/qwen3.5-9b | 8.52 | 12.77 | 20.15AITunnel | 262 144 |
Reka Edgerekaai/reka-edge | 8.52 | 8.52 | — | 16 384 |
Reka Flash 3rekaai/reka-flash-3 | 8.52 | 17.03 | — | 65 536 |
StepFun: Step 3.5 Flashstepfun/step-3.5-flash | 8.52 | 25.55 | — | 262 144 |
Qwen: Qwen3 VL 32B Instructqwen/qwen3-vl-32b-instruct | 8.86 | 35.43 | — | 131 072 |
Qwen: Qwen3 8Bqwen/qwen3-8b | 9.96 | 38.75 | — | 131 072 |
Qwen: Qwen3 VL 8B Instructqwen/qwen3-vl-8b-instruct | 9.96 | 38.75 | — | 262 144 |
Qwen: Qwen3 14Bqwen/qwen3-14b | 10.22 | 20.44 | 48.35VseGPT | 131 072 |
Qwen: Qwen3 Coder Nextqwen/qwen3-coder-next | 10.22 | 68.13 | 22.16AITunnel | 262 144 |
VoyageAI by MongoDB: voyage-4-largevoyageai/voyage-4-large | 10.22 | 0 | — | 32 000 |
VoyageAI by MongoDB: voyage-code-4voyageai/voyage-code-4 | 10.22 | 0 | — | 32 000 |
VoyageAI by MongoDB: voyage-multimodal-3.5voyageai/voyage-multimodal-3.5 | 10.22 | 0 | — | 32 000 |
Google: Gemini 3.1 Flash Lite (batch)google/gemini-3.1-flash-lite:batch | 10.65 | 63.87 | 20.40BotHub | 1 048 576 |
OpenAI: GPT-5 Mini (batch)openai/gpt-5-mini:batch | 10.65 | 85.16 | 20.40BotHub | 400 000 |
Выбор модели под задачу — не вопрос вкуса, а вопрос счёта в конце месяца. По горизонтали смешанная цена 3:1: три токена входа на один выхода, средний профиль обращения к чату. Шкала логарифмическая, иначе весь каталог слипся бы в первый столбец.
В шкалу не попали 84 бесплатных моделей.