AI21: Jamba Large 1.7 vs ScaleDown: Summarize

Neither wins outright: AI21: Jamba Large 1.7 is the pick when you need tool / function calling, ScaleDown: Summarize when cost matters at scale.

Key numbers

SpecAI21: Jamba Large 1.7ScaleDown: Summarize
ProviderAI21Scaledown
Input price (per 1M tokens)$2.00$0.04
Output price (per 1M tokens)$8.00$0
Blended price (3:1 input/output)$3.50$0.03
Cheaper than … of all models we track18%89%
Context window256K tokens (~384 pages)1M tokens (~1,500 pages)
Larger context than … of all models45%69%
Max output per response4K tokens (~3,100 words)4K tokens (~3,000 words)
Input typestexttext, image, file
Output typestexttext
Free variantNoNo
Listed since2025-08-082026-10-13

What it costs for real workloads

Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.

Workload (per month)AI21: Jamba Large 1.7ScaleDown: SummarizeDifference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$310$3.00ScaleDown: Summarize saves $307
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$320$4.80ScaleDown: Summarize saves $315
Coding / tool-using agent
2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens)
$336$4.80ScaleDown: Summarize saves $331
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$208$3.20ScaleDown: Summarize saves $205
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$108$2.00ScaleDown: Summarize saves $106

Capabilities side by side

CapabilityAI21: Jamba Large 1.7ScaleDown: SummarizeWhat it lets you do
Tool / function calling✓ Yes—call your APIs and run agent loops
Structured output (JSON schema)✓ Yes—return JSON that validates against your schema
Reasoning / thinking mode——spend extra tokens thinking before answering hard problems
Image input—✓ Yesread screenshots, charts and scanned pages
Audio input——take speech or audio directly
File / PDF input—✓ Yesaccept documents without your own parsing step
Image output——generate images, not just text
Built-in web search——answer from live web results
Seed (reproducible sampling)——repeat a generation for tests and evals
Log-probabilities——read token confidence for classification and scoring

From each model's published parameters and input/output types. “—” means not advertised, not proven absent.

Price history

Which should you choose?

Choose AI21: Jamba Large 1.7 if…

  • you need tool / function calling — to call your APIs and run agent loops; ScaleDown: Summarize does not advertise it
  • you need structured output (JSON schema) — to return JSON that validates against your schema; ScaleDown: Summarize does not advertise it

Choose ScaleDown: Summarize if…

  • cost matters at scale — it is 99% cheaper on a typical 3:1 input/output mix ($3.00 vs $310 a month for 50,000 support chats)
  • you need to fit long inputs in one request — 1M tokens is roughly 1,500 pages, against 384
  • you need image input — to read screenshots, charts and scanned pages; AI21: Jamba Large 1.7 does not advertise it
  • you need file / PDF input — to accept documents without your own parsing step; AI21: Jamba Large 1.7 does not advertise it
  • you want the newer model — released 2026-10-13, 14 months after the other

Frequently asked questions

Is AI21: Jamba Large 1.7 better than ScaleDown: Summarize?

Neither wins outright: AI21: Jamba Large 1.7 is the pick when you need tool / function calling, ScaleDown: Summarize when cost matters at scale. In short: AI21: Jamba Large 1.7 when you need tool / function calling, you need structured output (JSON schema); ScaleDown: Summarize when cost matters at scale, you need to fit long inputs in one request, you need image input, you need file / PDF input, you want the newer model.

Which is cheaper, AI21: Jamba Large 1.7 or ScaleDown: Summarize?

ScaleDown: Summarize is cheaper: $0.03 vs $3.50 per 1M tokens at a typical 3:1 input/output mix, 99% less. For 50,000 support conversations a month that is $3.00 against $310.

How much do AI21: Jamba Large 1.7 and ScaleDown: Summarize cost per million tokens?

AI21: Jamba Large 1.7 costs $2.00 per 1M input tokens and $8.00 per 1M output tokens; ScaleDown: Summarize costs $0.04 input and $0 output. Output tokens are billed separately, so long answers shift the gap.

Which has the bigger context window, AI21: Jamba Large 1.7 or ScaleDown: Summarize?

ScaleDown: Summarize: 1M tokens, about 1,500 pages, against 256K (about 384 pages) for AI21: Jamba Large 1.7.

Do AI21: Jamba Large 1.7 and ScaleDown: Summarize support function calling and JSON output?

Tool calling — AI21: Jamba Large 1.7: yes, ScaleDown: Summarize: not advertised. JSON-schema structured output — AI21: Jamba Large 1.7: yes, ScaleDown: Summarize: not advertised.

Can AI21: Jamba Large 1.7 or ScaleDown: Summarize read images?

Only ScaleDown: Summarize accepts image input; AI21: Jamba Large 1.7 is text-only for input.

Is AI21: Jamba Large 1.7 or ScaleDown: Summarize free to use?

No free variant is listed for either; both are pay-per-token.

What is the maximum output length of AI21: Jamba Large 1.7 and ScaleDown: Summarize?

AI21: Jamba Large 1.7 can write up to 4K tokens (about 3,100 words) per response; ScaleDown: Summarize up to 4K (about 3,000 words).

When were AI21: Jamba Large 1.7 and ScaleDown: Summarize released?

AI21: Jamba Large 1.7 was listed on 2025-08-08; ScaleDown: Summarize on 2026-10-13.

About the two models

Compare AI21: Jamba Large 1.7 with other models

Compare ScaleDown: Summarize with other models

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