Which is cheaper, GPT-5 mini or Jamba 1.5 Large?
As of August 25, 2026, GPT-5 mini is 78% cheaper on blended LLM API pricing. GPT-5 mini costs $0.25 per million input tokens and $2.00 per million output tokens ($2.25 blended 1M-in + 1M-out). Jamba 1.5 Large costs $2.00 / $8.00 per million tokens ($10.00 blended). Sources: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-pricing. The cheapest LLM for your app still depends on how many output tokens you generate.
How much does GPT-5 mini vs Jamba 1.5 Large cost per million tokens?
GPT-5 mini OpenAI API pricing is $0.25 input and $2.00 output per million tokens via OpenAI. Jamba 1.5 Large AI21 Labs API pricing is $2.00 input and $8.00 output per million tokens via AI21 Labs. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, GPT-5 mini or Jamba 1.5 Large?
GPT-5 mini has a published SWE-bench Verified score of 64.7%. Jamba 1.5 Large does not have that eval on this page yet.
What is the context window for GPT-5 mini vs Jamba 1.5 Large?
GPT-5 mini supports a 400K token context window, while Jamba 1.5 Large supports 256K tokens. GPT-5 mini offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.
Which model performs better on benchmarks, GPT-5 mini or Jamba 1.5 Large?
GPT-5 mini leads on 6 of 6 shared benchmarks versus Jamba 1.5 Large's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.
Is GPT-5 mini or Jamba 1.5 Large better for production use?
Both GPT-5 mini and Jamba 1.5 Large are production API models. For cost-sensitive production traffic, GPT-5 mini has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.
Can I switch between GPT-5 mini and Jamba 1.5 Large in my app?
Yes. Call GPT-5 mini through OpenAI and Jamba 1.5 Large through AI21 Labs with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.
How accurate is this GPT-5 mini vs Jamba 1.5 Large pricing data?
List rates are the latest published OpenAI API pricing and AI21 Labs API pricing, quoted per million tokens. Official rate sheets: https://developers.openai.com/api/docs/pricing and https://anotherwrapper.com/tools/llm-pricing. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.
What is the output token limit for GPT-5 mini and Jamba 1.5 Large?
GPT-5 mini supports up to 128K output tokens per request, while Jamba 1.5 Large supports up to 256K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.
Which model has better throughput, GPT-5 mini or Jamba 1.5 Large?
GPT-5 mini runs at approximately 200 tokens/second while Jamba 1.5 Large runs at 42 tokens/second. GPT-5 mini is faster in raw throughput. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.
How do I switch the models in this GPT-5 mini vs Jamba 1.5 Large comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open GPT-5 mini or Jamba 1.5 Large from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.
