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opencode_go/hy4-preview 1.024M context $0.834/M input $2.501/M output

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opencode_go/hy3 192K context $0.14/M input $0.58/M output

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opencode_go/step-5-preview 1M context $1/M input $2.7/M output

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opencode_go/beam-free 1.04858M context Input not listed Output not listed

LFM2.5-2.6B is a compact reasoning model from Liquid AI. It is suited for agent workflows, data extraction, RAG, and long-context processing. Liquid advises against using it for agentic coding or...

liquid/lfm-2.5-2.6b 128K context $0.35/M input $0.5/M output

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cerebras/llama-3.1-70b 128K context $0.6/M input $0.6/M output

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cerebras/llama-3.1-8b 128K context $0.1/M input $0.1/M output

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mistral/zai-glm-5-3-flash 1.04858M context $0.15/M input $0.5/M output

GPT-6.1 Terra is the mid-tier model in OpenAI's GPT-6.1 series, priced below GPT-6.1 Sol. It is suited for everyday agentic, coding, and writing work, is particularly strong at understanding screenshots...

openai/gpt-6.1-terra:batch 1.05M context $0.5/M input $2.5/M output

GPT-6.1 Terra Pro is the same underlying model as [GPT-6.1 Terra](https://openrouter.ai/openai/gpt-6.1-terra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. **Cost note:** pro mode spends far more...

openai/gpt-6.1-terra-pro 1.05M context $1/M input $5/M output

GPT-6.1 Terra Pro is the same underlying model as [GPT-6.1 Terra](https://openrouter.ai/openai/gpt-6.1-terra), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. **Cost note:** pro mode spends far more...

openai/gpt-6.1-terra-pro:batch 1.05M context $0.5/M input $2.5/M output

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abliteration/abliterated-model 262.144K context $1/M input $3/M output

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refuseless/glm-5.3-abliterated 1.04858M context $1.25/M input $2.25/M output

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refuseless/deepseek-v4.1-flash-fast 1.04858M context $0.05/M input $0.15/M output

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refuseless/minimax-m3.1-flash 1.04858M context $0.05/M input $0.25/M output

Ternary Bonsai 2 9B is PrismML’s compact, open-weight language model for conversational AI, reasoning, and tool use. Built on Qwen3.5, it uses ternary weights packed into 2 bits for efficient...

prism-ml/ternary-bonsai-2-9b 262.144K context $0.08/M input $0.13/M output

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morph/morph-kimik3 1.04858M context $2.5/M input $14/M output

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morph/morph-kimik3-fast 1.04858M context $6/M input $22.5/M output

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morph/morph-glm53-744b 1.04858M context $1.19/M input $6/M output

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morph/morph-glm53flash 1.04858M context $0.2/M input $0.7/M output

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morph/morph-dsv41flash 1.04858M context $0.12/M input $0.8/M output

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morph/morph-dsv41flash-1017 1.04858M context $0.12/M input $0.8/M output

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morph/morph-dsv41flash-abliterated 1.04858M context $0.3/M input $1.2/M output

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morph/morph-dsv4flash 1.04858M context $0.142/M input $0.4/M output

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aiand/deepseek-ai/deepseek-v4-flash 1.04858M context $0.15/M input $0.25/M output

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aiand/deepseek-ai/deepseek-v4-pro 1.04858M context $1/M input $2.5/M output

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aiand/google/gemma-4-31b-it 262.144K context $0.2/M input $0.5/M output