This model is deprecated. We only continue performance benchmarking for the default 10k input token workload. Results for other workloads are historical and no longer updated.

AI21 Labs has launched a newer model, Jamba 1.7 Large. We suggest considering it instead.

For more information, see comparison of Jamba 1.7 Large to other models and API provider benchmarks for Jamba 1.7 Large.

Jamba 1.6 Large logo
AI21 Labs
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Open weights model

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Released March 2025

Jamba 1.6 Large API 服务商基准测试与分析

模型比较

本分析旨在帮助你根据使用场景，选择 Jamba 1.6 Large 的最佳 API 服务商。

速度最快

输出速度

共 0 家服务商

延迟最低

首 Token 延迟

共 0 家服务商

价格最低

每 100 万 token 的混合价格

共 0 家服务商

目前没有可用的 Jamba 1.6 Large API 服务商。

该模型暂无服务商基准测试数据。

有关模型详情及其与其他模型的智能比较，请参阅 Jamba 1.6 Large 的模型页面。

亮点

速度

Output tokens per second · Higher is better
No data available

端到端响应时间

Seconds · Lower is better
No data available

价格

USD per 1M tokens (blended) · Lower is better
No data available

价格

Pricing: Cache Hit, Input, and Output

Price (USD per M Tokens) · Lower is better · 10,000 input tokens
No data available

Price per token for cached prompts (previously processed), typically offering a significant discount compared to regular input price, represented as USD per million tokens. The values shown here are the cache hit price; cache write and cache storage are billed separately and vary by provider — see "Cache pricing by provider" for detail.

Pricing: Blended Price

Blended at 7:2:1 (cache-input-output) · USD per 1M tokens (blended) · Lower is better
No data available

Price per token, shown in USD per million tokens. Price is a blend of cache hit, input, and output token prices using the selected ratio (default 7:2:1 cache-input-output).

Output Speed vs. Price

Blended at 7:2:1 (cache-input-output) · Output speed: output tokens per second · USD per 1M tokens (blended)
Most attractive quadrant
No data available

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

速度

按输出速度（每秒 token 数）衡量

Output Speed: Jamba 1.6 Large

Output speed: output tokens per second · 10,000 input tokens
No data available

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

Figures represent performance of the model's first-party API (e.g. OpenAI for o1) or the median across providers where a first-party API is not available (e.g. Meta's Llama models).

Latency vs. Output Speed

Latency: seconds to first token received · Output speed: output tokens per second · 10,000 input tokens
Most attractive quadrant
No data available

Tokens per second received while the model is generating tokens (ie. after first chunk has been received from the API for models which support streaming).

延迟

按首 Token 延迟（秒）衡量

首 Token 延迟

Seconds to first token received · Lower is better · 10,000 input tokens
No data available

Time to first token received, in seconds, after API request sent. For reasoning models which share reasoning tokens, this will be the first reasoning token. For models which do not support streaming, this represents time to receive the completion.

Figures represent median (P50) measurement over the past 72 hours to reflect sustained changes in performance.

端到端响应时间

Seconds to output 500 tokens, calculated based on time to first token, 'thinking' time for reasoning models, and output speed

端到端响应时间

Seconds to output 500 tokens, including reasoning model 'thinking' time · Lower is better · 10,000 input tokens
No data available

Seconds to receive a 500 token response. Key components:

  • Input time: Time to receive the first response token
  • Thinking time (only for reasoning models): Time reasoning models spend outputting tokens to reason prior to providing an answer. Amount of tokens based on the average reasoning tokens across a diverse set of 60 prompts (methodology details).
  • Answer time: Time to generate 500 output tokens, based on output speed

关键比较指标与 API 功能

No results.

常见问题

关于 Jamba 1.6 Large 服务商的常见问题

目前我们进行基准测试的 API 服务商均未提供 Jamba 1.6 Large。该模型为开放权重模型，可以自行托管。