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
XingChen: Xing4.0 29B A4B (free)
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$23.00
$0
XingChen: Xing4.0 29B A4B (free) saves $23.00
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$28.00
$0
XingChen: Xing4.0 29B A4B (free) saves $28.00
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)
$28.80
$0
XingChen: Xing4.0 29B A4B (free) saves $28.80
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$18.40
$0
XingChen: Xing4.0 29B A4B (free) saves $18.40
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$10.40
$0
XingChen: Xing4.0 29B A4B (free) saves $10.40
Capabilities side by side
Capability
Google: Gemma 4 31B
XingChen: Xing4.0 29B A4B (free)
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
—
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
✓ 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.
XingChen: Xing4.0 29B A4B (free): price unchanged since we started tracking it on 2026-10-17.
Date
Model
Input / 1M
Output / 1M
2026-10-15
Google: Gemma 4 31B
$0.20
$0.40
2026-08-27
Google: Gemma 4 31B
$0.09
$0.34
2026-08-21
Google: Gemma 4 31B
$0.10
$0.34
2026-08-19
Google: Gemma 4 31B
$0.09
$0.34
Which should you choose?
Choose Google: Gemma 4 31B if…
you need image input — to read screenshots, charts and scanned pages; XingChen: Xing4.0 29B A4B (free) does not advertise it
you need log-probabilities — to read token confidence for classification and scoring; XingChen: Xing4.0 29B A4B (free) does not advertise it
Choose XingChen: Xing4.0 29B A4B (free) if…
cost matters at scale — it is 100% cheaper on a typical 3:1 input/output mix ($0 vs $23.00 a month for 50,000 support chats)
you generate long outputs in one go — up to 236K tokens (about 176,900 words) per response
you want the newer model — released 2026-10-16, 7 months after the other
Frequently asked questions
Is Google: Gemma 4 31B better than XingChen: Xing4.0 29B A4B (free)?
Neither wins outright: Google: Gemma 4 31B is the pick when you need image input, XingChen: Xing4.0 29B A4B (free) when cost matters at scale. In short: Google: Gemma 4 31B when you need image input, you need log-probabilities; XingChen: Xing4.0 29B A4B (free) when cost matters at scale, you generate long outputs in one go, you want the newer model.
Which is cheaper, Google: Gemma 4 31B or XingChen: Xing4.0 29B A4B (free)?
XingChen: Xing4.0 29B A4B (free) is cheaper: $0 vs $0.25 per 1M tokens at a typical 3:1 input/output mix, 100% less. For 50,000 support conversations a month that is $0 against $23.00.
How much do Google: Gemma 4 31B and XingChen: Xing4.0 29B A4B (free) cost per million tokens?
Google: Gemma 4 31B costs $0.20 per 1M input tokens and $0.40 per 1M output tokens; XingChen: Xing4.0 29B A4B (free) costs $0 input and $0 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Google: Gemma 4 31B or XingChen: Xing4.0 29B A4B (free)?
Both take 262K tokens per request — roughly 393 pages of text.
Do Google: Gemma 4 31B and XingChen: Xing4.0 29B A4B (free) support function calling and JSON output?
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...
Xing4.0-29B-A4B is an open-weight mixture-of-experts language model from China Telecom's AI team (TeleAI) and the successor to the TeleChat series. It has 29B total parameters with 4B active per token...