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.
AI21: Jamba Large 1.7 vs Google: Gemma 4 31B (batch)
Google: Gemma 4 31B (batch) comes out ahead on the data we track: 5 advantages and none for AI21: Jamba Large 1.7.
Key numbers
| Spec | AI21: Jamba Large 1.7 | Google: Gemma 4 31B (batch) |
|---|---|---|
| Provider | AI21 | |
| Input price (per 1M tokens) | $2.00 | $0.39 |
| Output price (per 1M tokens) | $8.00 | $0.97 |
| Blended price (3:1 input/output) | $3.50 | $0.53 |
| Cheaper than … of all models we track | 18% | 52% |
| Context window | 256K tokens (~384 pages) | 262K tokens (~393 pages) |
| Larger context than … of all models | 45% | 48% |
| Max output per response | 4K tokens (~3,100 words) | 236K tokens (~176,900 words) |
| Input types | text | image, text, video |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2025-08-08 | 2026-04-02 |
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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 1.7 | Google: Gemma 4 31B (batch) | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $310 | $48.65 | Google: Gemma 4 31B (batch) saves $261 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $320 | $56.50 | Google: Gemma 4 31B (batch) saves $264 |
| 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 | $58.44 | Google: Gemma 4 31B (batch) saves $278 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $208 | $37.02 | Google: Gemma 4 31B (batch) saves $171 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $108 | $20.47 | Google: Gemma 4 31B (batch) saves $87.53 |
Capabilities side by side
| Capability | AI21: Jamba Large 1.7 | Google: Gemma 4 31B (batch) | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | ✓ Yes | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ 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) | — | — | 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.
- Google: Gemma 4 31B (batch): price unchanged since we started tracking it on 2026-08-29.
Which should you choose?
Choose Google: Gemma 4 31B (batch) if…
- cost matters at scale — it is 85% cheaper on a typical 3:1 input/output mix ($48.65 vs $310 a month for 50,000 support chats)
- you need reasoning / thinking mode — to spend extra tokens thinking before answering hard problems; AI21: Jamba Large 1.7 does not advertise it
- 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 236K tokens (about 176,900 words) per response
- you want the newer model — released 2026-04-02, 8 months after the other
Frequently asked questions
Is AI21: Jamba Large 1.7 better than Google: Gemma 4 31B (batch)?
Google: Gemma 4 31B (batch) comes out ahead on the data we track: 5 advantages and none for AI21: Jamba Large 1.7.
Which is cheaper, AI21: Jamba Large 1.7 or Google: Gemma 4 31B (batch)?
Google: Gemma 4 31B (batch) is cheaper: $0.53 vs $3.50 per 1M tokens at a typical 3:1 input/output mix, 85% less. For 50,000 support conversations a month that is $48.65 against $310.
How much do AI21: Jamba Large 1.7 and Google: Gemma 4 31B (batch) cost per million tokens?
AI21: Jamba Large 1.7 costs $2.00 per 1M input tokens and $8.00 per 1M output tokens; Google: Gemma 4 31B (batch) costs $0.39 input and $0.97 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, AI21: Jamba Large 1.7 or Google: Gemma 4 31B (batch)?
Google: Gemma 4 31B (batch): 262K tokens, about 393 pages, against 256K (about 384 pages) for AI21: Jamba Large 1.7.
Do AI21: Jamba Large 1.7 and Google: Gemma 4 31B (batch) support function calling and JSON output?
Tool calling — AI21: Jamba Large 1.7: yes, Google: Gemma 4 31B (batch): yes. JSON-schema structured output — AI21: Jamba Large 1.7: yes, Google: Gemma 4 31B (batch): yes.
Can AI21: Jamba Large 1.7 or Google: Gemma 4 31B (batch) read images?
Only Google: Gemma 4 31B (batch) accepts image input; AI21: Jamba Large 1.7 is text-only for input.
Is AI21: Jamba Large 1.7 or Google: Gemma 4 31B (batch) 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 Google: Gemma 4 31B (batch)?
AI21: Jamba Large 1.7 can write up to 4K tokens (about 3,100 words) per response; Google: Gemma 4 31B (batch) up to 236K (about 176,900 words).
When were AI21: Jamba Large 1.7 and Google: Gemma 4 31B (batch) released?
AI21: Jamba Large 1.7 was listed on 2025-08-08; Google: Gemma 4 31B (batch) on 2026-04-02.
About the two models
AI21: Jamba Large 1.7
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 →Google: Gemma 4 31B (batch)
Gemma 4 31B Instruct is Google DeepMind's 30.7B dense multimodal model supporting text and image input with text output. Features a 256K token context window, configurable thinking/reasoning mode, native function...
Full Google: Gemma 4 31B (batch) specs →