Neither wins outright: AI21: Jamba Large 1.7 is the pick when you need to fit long inputs in one request, NVIDIA: Nemotron 3.5 Content Safety when cost matters at scale.
| Spec | AI21: Jamba Large 1.7 | NVIDIA: Nemotron 3.5 Content Safety |
|---|---|---|
| Provider | AI21 | Nvidia |
| Input price (per 1M tokens) | $2.00 | $0.20 |
| Output price (per 1M tokens) | $8.00 | $0.20 |
| Blended price (3:1 input/output) | $3.50 | $0.20 |
| Cheaper than … of all models we track | 18% | 69% |
| Context window | 256K tokens (~384 pages) | 131K tokens (~197 pages) |
| Larger context than … of all models | 44% | 22% |
| Max output per response | 4K tokens (~3,100 words) | 118K tokens (~88,500 words) |
| Input types | text | text, image |
| Output types | text | text |
| Free variant | No | Yes |
| Listed since | 2025-08-08 | 2026-06-04 |
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 | NVIDIA: Nemotron 3.5 Content Safety | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $310 | $19.00 | NVIDIA: Nemotron 3.5 Content Safety saves $291 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $320 | $26.00 | NVIDIA: Nemotron 3.5 Content Safety saves $294 |
| 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 | $26.40 | NVIDIA: Nemotron 3.5 Content Safety saves $310 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $208 | $17.20 | NVIDIA: Nemotron 3.5 Content Safety saves $191 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $108 | $10.20 | NVIDIA: Nemotron 3.5 Content Safety saves $97.80 |
| Capability | AI21: Jamba Large 1.7 | NVIDIA: Nemotron 3.5 Content Safety | 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 | — | ✓ Yes | 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 | — | — | 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) | — | ✓ Yes | 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.
Neither wins outright: AI21: Jamba Large 1.7 is the pick when you need to fit long inputs in one request, NVIDIA: Nemotron 3.5 Content Safety when cost matters at scale. In short: AI21: Jamba Large 1.7 when you need to fit long inputs in one request, you need tool / function calling, you need structured output (JSON schema); NVIDIA: Nemotron 3.5 Content Safety when cost matters at scale, you need reasoning / thinking mode, you need image input, you need seed (reproducible sampling), you generate long outputs in one go, you want to prototype at zero cost, you want the newer model.
NVIDIA: Nemotron 3.5 Content Safety is cheaper: $0.20 vs $3.50 per 1M tokens at a typical 3:1 input/output mix, 94% less. For 50,000 support conversations a month that is $19.00 against $310.
AI21: Jamba Large 1.7 costs $2.00 per 1M input tokens and $8.00 per 1M output tokens; NVIDIA: Nemotron 3.5 Content Safety costs $0.20 input and $0.20 output. Output tokens are billed separately, so long answers shift the gap.
AI21: Jamba Large 1.7: 256K tokens, about 384 pages, against 131K (about 197 pages) for NVIDIA: Nemotron 3.5 Content Safety.
Tool calling — AI21: Jamba Large 1.7: yes, NVIDIA: Nemotron 3.5 Content Safety: not advertised. JSON-schema structured output — AI21: Jamba Large 1.7: yes, NVIDIA: Nemotron 3.5 Content Safety: not advertised.
Only NVIDIA: Nemotron 3.5 Content Safety accepts image input; AI21: Jamba Large 1.7 is text-only for input.
NVIDIA: Nemotron 3.5 Content Safety has a free variant (nvidia/nemotron-3.5-content-safety:free). Free variants usually carry tighter rate limits.
AI21: Jamba Large 1.7 can write up to 4K tokens (about 3,100 words) per response; NVIDIA: Nemotron 3.5 Content Safety up to 118K (about 88,500 words).
AI21: Jamba Large 1.7 was listed on 2025-08-08; NVIDIA: Nemotron 3.5 Content Safety on 2026-06-04.
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 →NVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses from LLMs and VLMs, accepting...
Full NVIDIA: Nemotron 3.5 Content Safety specs →