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 1.7
ScaleDown: Summarize
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$310
$3.00
ScaleDown: 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
$4.80
ScaleDown: 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
$4.80
ScaleDown: 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
$3.20
ScaleDown: 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
$2.00
ScaleDown: Summarize saves $106
Capabilities side by side
Capability
AI21: Jamba Large 1.7
ScaleDown: Summarize
What 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
—
✓ Yes
read screenshots, charts and scanned pages
Audio input
—
—
take speech or audio directly
File / PDF input
—
✓ Yes
accept 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
AI21: Jamba Large 1.7: price unchanged since we started tracking it on 2026-03-10.
ScaleDown: Summarize: price unchanged since we started tracking it on 2026-10-14.
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.
Jamba Large 1.7 is the latest model in the Jamba open family, offering improvements in grounding, instruction-following, and overall efficiency. Built on a hybrid SSM-Transformer architecture with a 256K context...
Summarize is an abstractive summarization model from ScaleDown. It condenses long text and documents into a fluent, faithful rewrite rather than lifting sentences from the source, and is suited for...