--- title: "codellama-7b Cost Calculator - Llamagate" description: "Calculate the cost of using codellama-7b from Llamagate. Input costs $0.06 and output $0.12 per 1M tokens." url: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate/model/codellama-7b" markdown: "https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate/model/codellama-7b.md" --- # codellama-7b Cost Calculator - Llamagate > Calculate the cost of using codellama-7b from Llamagate. Input costs $0.06 and output $0.12 per 1M tokens. ## Important Links - [View MCP Gateway](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/resources/mcp-gateway.md) - [Features](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/#features) - [Enterprise](https://www.getmaxim.ai/enterprise) - [Pricing](https://www.getmaxim.ai/pricing) - [Docs](https://docs.getbifrost.ai) - [GitHub](https://github.com/maximhq/bifrost) - [Book a Demo](https://www.getmaxim.ai/book-a-demo) ## About codellama-7b codellama-7b is a chat model from Llamagate, one of 14 chat models they offer. It is priced at $0.06 per 1M input tokens and $0.12 per 1M output tokens, ranking 202 out of 3254 chat models by cost and cheaper than 94% of models in this category. codellama-7b supports function calling, structured output. It accepts up to 16K input tokens. ## Pricing Published Llamagate pricing for codellama-7b. - **$0.06 / 1M tokens Input.** - **$0.12 / 1M tokens Output.** ## Technical Specifications - **Chat Mode.** - **16,384 Max Input Tokens.** - **4,096 Max Output Tokens.** - **4,096 Max Tokens.** ## Model Capabilities codellama-7b supports: Function Calling, Response Schema. ## How Pricing Compares At $0.06 per 1M input tokens and $0.12 per 1M output tokens, codellama-7b ranks 202 out of 3254 chat models by input cost. It is more affordable compared to the median of $0.52 for chat models, and is cheaper than 94% of models in this category. codellama-7b is one of 14 Llamagate chat models, with support for function calling, structured output. | Model | Provider | Input $/1M | Output $/1M | vs codellama-7b | | --- | --- | --- | --- | --- | | amazon.nova-lite-v1:0 | AWS Bedrock | $0.06 | $0.24 | 0% | | apac.amazon.nova-lite-v1:0 | AWS Bedrock | $0.06 | $0.25 | +5% | | gpt-5-nano-2025-08-07 | Azure | $0.06 | $0.44 | -8% | | gpt-5-nano | Azure | $0.05 | $0.40 | -17% | | gpt-oss-20b | Fireworks AI | $0.07 | $0.30 | +17% | ## More from Llamagate - [qwen2.5-coder-7b ($0.06/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate/model/qwen2.5-coder-7b.md) - [deepseek-coder-6.7b ($0.06/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate/model/deepseek-coder-6.7b.md) - [llama-3.2-3b ($0.04/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate/model/llama-3.2-3b.md) - [qwen3-8b ($0.04/1M input)](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate/model/qwen3-8b.md) ## Related Resources - [All Llamagate pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate.md) ## FAQ ### Is codellama-7b cheaper than amazon.nova-lite-v1:0? No. codellama-7b costs $0.06 per 1M input tokens while amazon.nova-lite-v1:0 costs $0.06 per 1M input tokens, making amazon.nova-lite-v1:0 0% more affordable for input. However, codellama-7b may offer different capabilities or performance characteristics that justify the price difference. ### How does codellama-7b pricing compare to the average chat model? codellama-7b input pricing is $0.06 per 1M tokens, which is 88% below the median of $0.52 for chat models. It ranks 202 out of 3254 chat models by input cost, making it cheaper than 94% of models in this category. For output, it costs $0.12 per 1M tokens compared to the median of $1.50. ### What makes codellama-7b different from other Llamagate models? Among Llamagate's 14 chat models, codellama-7b ranks 7 by input cost. ### What are the best alternatives to codellama-7b? The most comparable chat models to codellama-7b are: amazon.nova-lite-v1:0 from AWS Bedrock ($0.06/1M input tokens); apac.amazon.nova-lite-v1:0 from AWS Bedrock ($0.06/1M input tokens); gpt-5-nano-2025-08-07 from Azure ($0.06/1M input tokens); gpt-5-nano from Azure ($0.05/1M 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 do I calculate codellama-7b costs? codellama-7b 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 $0.06 and generating 1M output tokens costs $0.12. ## Related Resources - [All Llamagate pricing](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate.md) - [LLM cost calculator](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator.md) - [Model library](https://maxim-root-proxy-preview.getmaxim.workers.dev/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) - [Enterprise: Bifrost enterprise](https://www.getmaxim.ai/enterprise) - [Book a Demo: Bifrost demo](https://www.getmaxim.ai/book-a-demo) - [Resources: Bifrost resources](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/resources.md) --- *This is a markdown version of [https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate/model/codellama-7b](https://maxim-root-proxy-preview.getmaxim.workers.dev/bifrost/llm-cost-calculator/provider/llamagate/model/codellama-7b) for AI/LLM consumption.*