Neither wins outright: Google: Gemma 4 31B (batch) is the pick when cost matters at scale, Qwen: Qwen3.5-122B-A10B when you need seed (reproducible sampling).
| Spec | Google: Gemma 4 31B (batch) | Qwen: Qwen3.5-122B-A10B |
|---|---|---|
| Provider | Qwen | |
| Input price (per 1M tokens) | $0.39 | $0.26 |
| Output price (per 1M tokens) | $0.97 | $2.08 |
| Blended price (3:1 input/output) | $0.53 | $0.72 |
| Cheaper than … of all models we track | 52% | 47% |
| Context window | 262K tokens (~393 pages) | 262K tokens (~393 pages) |
| Larger context than … of all models | 48% | 48% |
| Max output per response | 236K tokens (~176,900 words) | 66K tokens (~49,200 words) |
| Input types | image, text, video | text, image, video |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2026-04-02 | 2026-02-25 |
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) | Google: Gemma 4 31B (batch) | Qwen: Qwen3.5-122B-A10B | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $48.65 | $61.10 | Google: Gemma 4 31B (batch) saves $12.45 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $56.50 | $52.00 | Qwen: Qwen3.5-122B-A10B saves $4.50 |
| 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) | $58.44 | $56.16 | Qwen: Qwen3.5-122B-A10B saves $2.28 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $37.02 | $33.28 | Qwen: Qwen3.5-122B-A10B saves $3.74 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $20.47 | $15.08 | Qwen: Qwen3.5-122B-A10B saves $5.39 |
| Capability | Google: Gemma 4 31B (batch) | Qwen: Qwen3.5-122B-A10B | 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 | ✓ Yes | spend extra tokens thinking before answering hard problems |
| Image input | ✓ Yes | ✓ 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 | — | ✓ Yes | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
| Date | Model | Input / 1M | Output / 1M |
|---|---|---|---|
| 2026-09-10 | Qwen: Qwen3.5-122B-A10B | $0.26 | $2.08 |
| 2026-08-29 | Qwen: Qwen3.5-122B-A10B | $0.29 | $2.40 |
| 2026-08-18 | Qwen: Qwen3.5-122B-A10B | $0.26 | $2.08 |
| 2026-08-07 | Qwen: Qwen3.5-122B-A10B | $0.29 | $2.40 |
Neither wins outright: Google: Gemma 4 31B (batch) is the pick when cost matters at scale, Qwen: Qwen3.5-122B-A10B when you need seed (reproducible sampling). In short: Google: Gemma 4 31B (batch) when cost matters at scale, you generate long outputs in one go; Qwen: Qwen3.5-122B-A10B when you need seed (reproducible sampling), you need log-probabilities.
Google: Gemma 4 31B (batch) is cheaper: $0.53 vs $0.72 per 1M tokens at a typical 3:1 input/output mix, 25% less. For 50,000 support conversations a month that is $48.65 against $61.10.
Google: Gemma 4 31B (batch) costs $0.39 per 1M input tokens and $0.97 per 1M output tokens; Qwen: Qwen3.5-122B-A10B costs $0.26 input and $2.08 output. Output tokens are billed separately, so long answers shift the gap.
Both take 262K tokens per request — roughly 393 pages of text.
Tool calling — Google: Gemma 4 31B (batch): yes, Qwen: Qwen3.5-122B-A10B: yes. JSON-schema structured output — Google: Gemma 4 31B (batch): yes, Qwen: Qwen3.5-122B-A10B: yes.
Yes, both accept image input.
No free variant is listed for either; both are pay-per-token.
Google: Gemma 4 31B (batch) can write up to 236K tokens (about 176,900 words) per response; Qwen: Qwen3.5-122B-A10B up to 66K (about 49,200 words).
Google: Gemma 4 31B (batch) was listed on 2026-04-02; Qwen: Qwen3.5-122B-A10B on 2026-02-25.
Google: Gemma 4 31B (batch): price unchanged since we started tracking it on 2026-08-29. Qwen: Qwen3.5-122B-A10B: input price cut 10% ($0.29 → $0.26/1M), output price cut 13% ($2.40 → $2.08/1M) on 2026-09-10 (4 price changes since 2026-03-10).
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...
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Full Qwen: Qwen3.5-122B-A10B specs →