AI21: Jamba Large 1.7 comes out ahead on the data we track: 2 advantages and none for sentence-transformers-testing/stsb-bert-tiny-safetensors.
| Spec | AI21: Jamba Large 1.7 | sentence-transformers-testing/stsb-bert-tiny-safetensors |
|---|---|---|
| Provider | AI21 | Hugging Face |
| Input price (per 1M tokens) | $2.00 | n/a |
| Output price (per 1M tokens) | $8.00 | n/a |
| Blended price (3:1 input/output) | $3.50 | n/a |
| Cheaper than … of all models we track | 18% | n/a |
| Context window | 256K tokens (~384 pages) | n/a |
| Larger context than … of all models | 45% | n/a |
| Max output per response | 4K tokens (~3,100 words) | n/a |
| Input types | text | text |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2025-08-08 | n/a |
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 | sentence-transformers-testing/stsb-bert-tiny-safetensors | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $310 | n/a | — |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $320 | n/a | — |
| 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 | n/a | — |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $208 | n/a | — |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $108 | n/a | — |
| Capability | AI21: Jamba Large 1.7 | sentence-transformers-testing/stsb-bert-tiny-safetensors | 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 | — | — | read 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.
No advantage on the data we track — pick it for provider preference or output quality on your own prompts.
AI21: Jamba Large 1.7 comes out ahead on the data we track: 2 advantages and none for sentence-transformers-testing/stsb-bert-tiny-safetensors.
Tool calling — AI21: Jamba Large 1.7: yes, sentence-transformers-testing/stsb-bert-tiny-safetensors: not advertised. JSON-schema structured output — AI21: Jamba Large 1.7: yes, sentence-transformers-testing/stsb-bert-tiny-safetensors: not advertised.
Neither accepts image input — both are text-in models.
No free variant is listed for either; both are pay-per-token.
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...
Full AI21: Jamba Large 1.7 specs →No description provided yet.
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