--- title: "qwen3.8-27b Cost Calculator - Streamlake" description: "Calculate the cost of using qwen3.8-27b from Streamlake. Input costs $0.50 and output $3.00 per 1M tokens." url: "https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake/model/qwen3.8-27b" markdown: "https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake/model/qwen3.8-27b.md" --- # qwen3.8-27b Cost Calculator - Streamlake > Calculate the cost of using qwen3.8-27b from Streamlake. Input costs $0.50 and output $3.00 per 1M tokens. ## Important Links - [View MCP Gateway](https://www.getmaxim.ai/resources/mcp-gateway.md) - [Features](https://www.getmaxim.ai/bifrost/#features) - [Enterprise](https://www.getmaxim.ai/enterprise) - [Pricing](https://www.getmaxim.ai/pricing.md) - [Docs](https://docs.getbifrost.ai) - [GitHub](https://github.com/maximhq/bifrost) - [Book a Demo](https://www.getmaxim.ai/book-a-demo) ## About qwen3.8-27b qwen3.8-27b is a chat model from Streamlake, one of 26 chat models they offer. It is priced at $0.50 per 1M input tokens and $3.00 per 1M output tokens, ranking 1908 out of 4040 chat models by cost and cheaper than 52% of models in this category. qwen3.8-27b supports vision, function calling, reasoning, prompt caching. Its 984K-token context window is in the top 30% among chat models. ## Pricing Published Streamlake pricing for qwen3.8-27b. - **$0.50 / 1M tokens Input.** - **$3.00 / 1M tokens Output.** ## Technical Specifications - **Chat Mode.** - **983,616 Max Input Tokens.** - **128,000 Max Output Tokens.** ## Model Capabilities qwen3.8-27b supports: Function Calling, Vision, Reasoning, Prompt Caching. ## How Pricing Compares At $0.50 per 1M input tokens and $3.00 per 1M output tokens, qwen3.8-27b ranks 1908 out of 4040 chat models by input cost. It is more affordable compared to the median of $0.60 for chat models, and is cheaper than 52% of models in this category. qwen3.8-27b is one of 26 Streamlake chat models, with support for vision, function calling, reasoning, prompt caching. its 984K-token context window places it in the top 30% of chat models. | Model | Provider | Input $/1M | Output $/1M | vs qwen3.8-27b | | --- | --- | --- | --- | --- | | eu.amazon.nova-2-lite-v1:0 | AWS Bedrock | $0.43 | $3.60 | -14% | | kimi-k2.6 | Azure | $0.60 | $3.00 | +20% | | gemma-4-31B-it | Sail | $0.40 | $0.60 | -20% | | gemini-3-flash-preview | Vertex AI | $0.50 | $3.00 | 0% | | gemini-3-flash-preview | Google Gemini | $0.50 | $3.00 | 0% | ## More from Streamlake - [deepseek-v4-flash-0731 ($0.44/1M input)](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake/model/deepseek-v4-flash-0731.md) - [mimo-v2.6-pro ($0.43/1M input)](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake/model/mimo-v2.6-pro.md) - [Kimi-K2-Instruct-0905 ($0.57/1M input)](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake/model/kimi-k2-instruct-0905.md) - [deepseek-r1 ($0.57/1M input)](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake/model/deepseek-r1.md) ## Related Resources - [All Streamlake pricing](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake.md) ## FAQ ### Is qwen3.8-27b cheaper than eu.amazon.nova-2-lite-v1:0? No. qwen3.8-27b costs $0.50 per 1M input tokens while eu.amazon.nova-2-lite-v1:0 costs $0.43 per 1M input tokens, making eu.amazon.nova-2-lite-v1:0 14% more affordable for input. However, qwen3.8-27b may offer different capabilities or performance characteristics that justify the price difference. ### How does qwen3.8-27b pricing compare to the average chat model? qwen3.8-27b input pricing is $0.50 per 1M tokens, which is 17% below the median of $0.60 for chat models. It ranks 1908 out of 4040 chat models by input cost, making it cheaper than 52% of models in this category. For output, it costs $3.00 per 1M tokens compared to the median of $1.80. ### What makes qwen3.8-27b different from other Streamlake models? Among Streamlake's 26 chat models, qwen3.8-27b ranks 11 by input cost. ### What are the best alternatives to qwen3.8-27b? The most comparable chat models to qwen3.8-27b are: eu.amazon.nova-2-lite-v1:0 from AWS Bedrock ($0.43/1M input tokens); kimi-k2.6 from Azure ($0.60/1M input tokens); gemma-4-31B-it from Sail ($0.40/1M input tokens); gemini-3-flash-preview from Vertex AI ($0.50/1M input tokens). These alternatives were selected based on similar capabilities, pricing, and provider diversity. You can compare any of these models in detail using the Bifrost Model Library. ### How large is qwen3.8-27b's context window? qwen3.8-27b supports up to 983,616 input tokens, placing it in the top 30% of chat models by context window size (rank 1119 of 3774). This makes it suitable for processing long documents, extensive code repositories, or maintaining detailed conversation histories. ### How do I calculate qwen3.8-27b costs? qwen3.8-27b is priced based on input and output tokens. Use the interactive calculator at the top of this page to estimate costs for your specific workload. Enter your expected input and output tokens volume and the calculator will show the total cost breakdown. For reference, processing 1M input tokens costs $0.50 and generating 1M output tokens costs $3.00. ## Related Resources - [All Streamlake pricing](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake.md) - [LLM cost calculator](https://www.getmaxim.ai/bifrost/llm-cost-calculator.md) - [Model library](https://www.getmaxim.ai/bifrost/model-library.md) - [Docs: Bifrost docs](https://docs.getbifrost.ai) - [GitHub: maximhq/bifrost](https://github.com/maximhq/bifrost) - [Pricing: Bifrost pricing](https://www.getmaxim.ai/pricing.md) - [Enterprise: Bifrost enterprise](https://www.getmaxim.ai/enterprise) - [Book a Demo: Bifrost demo](https://www.getmaxim.ai/book-a-demo) - [Resources: Bifrost resources](https://www.getmaxim.ai/resources.md) --- *This is a markdown version of [https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake/model/qwen3.8-27b](https://www.getmaxim.ai/bifrost/llm-cost-calculator/provider/streamlake/model/qwen3.8-27b) for AI/LLM consumption.*