AI21: Jamba Large 1.7 vs Pareto 26.9

Pareto 26.9 comes out ahead on the data we track: 3 advantages and none for AI21: Jamba Large 1.7.

Key numbers

SpecAI21: Jamba Large 1.7Pareto 26.9
ProviderAI21Unbiased
Input price (per 1M tokens)$2.00$2.50
Output price (per 1M tokens)$8.00$7.50
Blended price (3:1 input/output)$3.50$3.75
Cheaper than … of all models we track18%17%
Context window256K tokens (~384 pages)262K tokens (~393 pages)
Larger context than … of all models45%48%
Max output per response4K tokens (~3,100 words)131K tokens (~98,300 words)
Input typestexttext, image
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 1.7Pareto 26.9Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$310$338AI21: Jamba Large 1.7 saves $27.50
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$320$375AI21: Jamba Large 1.7 saves $55.00
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$390AI21: Jamba Large 1.7 saves $54.00
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$208$245AI21: Jamba Large 1.7 saves $37.00
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$108$133AI21: Jamba Large 1.7 saves $24.50

Capabilities side by side

CapabilityAI21: Jamba Large 1.7Pareto 26.9What it lets you do
Tool / function calling✓ Yes✓ Yescall your APIs and run agent loops
Structured output (JSON schema)✓ Yes✓ Yesreturn 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——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

Which should you choose?

Choose AI21: Jamba Large 1.7 if…

No advantage on the data we track — pick it for provider preference or output quality on your own prompts.

Choose Pareto 26.9 if…

  • you need image input — to read screenshots, charts and scanned pages; AI21: Jamba Large 1.7 does not advertise it
  • you generate long outputs in one go — up to 131K tokens (about 98,300 words) per response
  • 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 Pareto 26.9?

Pareto 26.9 comes out ahead on the data we track: 3 advantages and none for AI21: Jamba Large 1.7.

Which is cheaper, AI21: Jamba Large 1.7 or Pareto 26.9?

AI21: Jamba Large 1.7 is cheaper: $3.50 vs $3.75 per 1M tokens at a typical 3:1 input/output mix, 7% less. For 50,000 support conversations a month that is $310 against $338.

How much do AI21: Jamba Large 1.7 and Pareto 26.9 cost per million tokens?

AI21: Jamba Large 1.7 costs $2.00 per 1M input tokens and $8.00 per 1M output tokens; Pareto 26.9 costs $2.50 input and $7.50 output. Output tokens are billed separately, so long answers shift the gap.

Which has the bigger context window, AI21: Jamba Large 1.7 or Pareto 26.9?

Pareto 26.9: 262K tokens, about 393 pages, against 256K (about 384 pages) for AI21: Jamba Large 1.7.

Do AI21: Jamba Large 1.7 and Pareto 26.9 support function calling and JSON output?

Tool calling — AI21: Jamba Large 1.7: yes, Pareto 26.9: yes. JSON-schema structured output — AI21: Jamba Large 1.7: yes, Pareto 26.9: yes.

Can AI21: Jamba Large 1.7 or Pareto 26.9 read images?

Only Pareto 26.9 accepts image input; AI21: Jamba Large 1.7 is text-only for input.

Is AI21: Jamba Large 1.7 or Pareto 26.9 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 Pareto 26.9?

AI21: Jamba Large 1.7 can write up to 4K tokens (about 3,100 words) per response; Pareto 26.9 up to 131K (about 98,300 words).

When were AI21: Jamba Large 1.7 and Pareto 26.9 released?

AI21: Jamba Large 1.7 was listed on 2025-08-08; Pareto 26.9 on 2026-10-13.

About the two models

Unbiased

Pareto 26.9

Pareto is a multimodal composite model built for research, coding, and agentic workflows, while delivering frontier-level performance across a broad range of general-purpose tasks.

Full Pareto 26.9 specs →

Compare AI21: Jamba Large 1.7 with other models

Compare Pareto 26.9 with other models

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