Which is cheaper, Jamba 1.5 Large or Mercury 2?
As of August 25, 2026, Mercury 2 is 90% cheaper on blended LLM API pricing. Mercury 2 costs $0.25 per million input tokens and $0.75 per million output tokens ($1.00 blended 1M-in + 1M-out). Jamba 1.5 Large costs $2.00 / $8.00 per million tokens ($10.00 blended). Sources: https://anotherwrapper.com/tools/llm-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 Jamba 1.5 Large vs Mercury 2 cost per million tokens?
Jamba 1.5 Large AI21 Labs API pricing is $2.00 input and $8.00 output per million tokens via AI21 Labs. Mercury 2 Inception API pricing is $0.25 input and $0.75 output per million tokens via Inception. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.
Which is better for coding, Jamba 1.5 Large or Mercury 2?
Mercury 2 has a published LiveCodeBench score of 67%. Jamba 1.5 Large does not have that eval on this page yet.
What is the context window for Jamba 1.5 Large vs Mercury 2?
Jamba 1.5 Large supports a 256K token context window, while Mercury 2 supports 128K tokens. Jamba 1.5 Large 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, Jamba 1.5 Large or Mercury 2?
Mercury 2 leads on 1 of 1 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 Jamba 1.5 Large or Mercury 2 better for production use?
Both Jamba 1.5 Large and Mercury 2 are production API models. For cost-sensitive production traffic, Mercury 2 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 Jamba 1.5 Large and Mercury 2 in my app?
Yes. Call Jamba 1.5 Large through AI21 Labs and Mercury 2 through Inception 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 Jamba 1.5 Large vs Mercury 2 pricing data?
List rates are the latest published AI21 Labs API pricing and Inception API pricing, quoted per million tokens. Official rate sheets: https://anotherwrapper.com/tools/llm-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 Jamba 1.5 Large and Mercury 2?
Jamba 1.5 Large supports up to 256K output tokens per request, while Mercury 2 supports up to 8K 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, Jamba 1.5 Large or Mercury 2?
Jamba 1.5 Large runs at approximately 42 tokens/second while Mercury 2 runs at 1009 tokens/second. Mercury 2 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 Jamba 1.5 Large vs Mercury 2 comparison?
Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Jamba 1.5 Large or Mercury 2 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.