Google: Gemini 2.5 Flash Lite (batch) vs MiniMax: MiniMax M3.1 Flash
Neither wins outright: Google: Gemini 2.5 Flash Lite (batch) is the pick when cost matters at scale, MiniMax: MiniMax M3.1 Flash when you need log-probabilities.
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: Gemini 2.5 Flash Lite (batch)
MiniMax: MiniMax M3.1 Flash
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$7.75
$23.25
Google: Gemini 2.5 Flash Lite (batch) saves $15.50
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$8.00
$24.00
Google: Gemini 2.5 Flash Lite (batch) saves $16.00
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)
$8.40
$25.20
Google: Gemini 2.5 Flash Lite (batch) saves $16.80
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$5.20
$15.60
Google: Gemini 2.5 Flash Lite (batch) saves $10.40
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$2.70
$8.10
Google: Gemini 2.5 Flash Lite (batch) saves $5.40
Capabilities side by side
Capability
Google: Gemini 2.5 Flash Lite (batch)
MiniMax: MiniMax M3.1 Flash
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
✓ Yes
—
take speech or audio directly
File / PDF input
✓ Yes
—
accept documents without your own parsing step
Image output
—
—
generate images, not just text
Built-in web search
✓ Yes
—
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.
Price history
Google: Gemini 2.5 Flash Lite (batch): price unchanged since we started tracking it on 2026-08-07.
MiniMax: MiniMax M3.1 Flash: price unchanged since we started tracking it on 2026-10-23.
Which should you choose?
Choose Google: Gemini 2.5 Flash Lite (batch) if…
cost matters at scale — it is 67% cheaper on a typical 3:1 input/output mix ($7.75 vs $23.25 a month for 50,000 support chats)
you need audio input — to take speech or audio directly; MiniMax: MiniMax M3.1 Flash does not advertise it
you need file / PDF input — to accept documents without your own parsing step; MiniMax: MiniMax M3.1 Flash does not advertise it
you need built-in web search — to answer from live web results; MiniMax: MiniMax M3.1 Flash does not advertise it
Choose MiniMax: MiniMax M3.1 Flash if…
you need log-probabilities — to read token confidence for classification and scoring; Google: Gemini 2.5 Flash Lite (batch) does not advertise it
you generate long outputs in one go — up to 524K tokens (about 393,200 words) per response
you want to prototype at zero cost — a free variant is listed
you want the newer model — released 2026-10-19, 15 months after the other
Frequently asked questions
Is Google: Gemini 2.5 Flash Lite (batch) better than MiniMax: MiniMax M3.1 Flash?
Neither wins outright: Google: Gemini 2.5 Flash Lite (batch) is the pick when cost matters at scale, MiniMax: MiniMax M3.1 Flash when you need log-probabilities. In short: Google: Gemini 2.5 Flash Lite (batch) when cost matters at scale, you need audio input, you need file / PDF input, you need built-in web search; MiniMax: MiniMax M3.1 Flash when you need log-probabilities, you generate long outputs in one go, you want to prototype at zero cost, you want the newer model.
Which is cheaper, Google: Gemini 2.5 Flash Lite (batch) or MiniMax: MiniMax M3.1 Flash?
Google: Gemini 2.5 Flash Lite (batch) is cheaper: $0.09 vs $0.26 per 1M tokens at a typical 3:1 input/output mix, 67% less. For 50,000 support conversations a month that is $7.75 against $23.25.
How much do Google: Gemini 2.5 Flash Lite (batch) and MiniMax: MiniMax M3.1 Flash cost per million tokens?
Google: Gemini 2.5 Flash Lite (batch) costs $0.05 per 1M input tokens and $0.20 per 1M output tokens; MiniMax: MiniMax M3.1 Flash costs $0.15 input and $0.60 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Google: Gemini 2.5 Flash Lite (batch) or MiniMax: MiniMax M3.1 Flash?
Both take 1.0M tokens per request — roughly 1,573 pages of text.
Do Google: Gemini 2.5 Flash Lite (batch) and MiniMax: MiniMax M3.1 Flash support function calling and JSON output?
Can Google: Gemini 2.5 Flash Lite (batch) or MiniMax: MiniMax M3.1 Flash read images?
Yes, both accept image input.
Is Google: Gemini 2.5 Flash Lite (batch) or MiniMax: MiniMax M3.1 Flash free to use?
MiniMax: MiniMax M3.1 Flash has a free variant (minimax/minimax-m3.1-flash:free). Free variants usually carry tighter rate limits.
What is the maximum output length of Google: Gemini 2.5 Flash Lite (batch) and MiniMax: MiniMax M3.1 Flash?
Google: Gemini 2.5 Flash Lite (batch) can write up to 66K tokens (about 49,200 words) per response; MiniMax: MiniMax M3.1 Flash up to 524K (about 393,200 words).
When were Google: Gemini 2.5 Flash Lite (batch) and MiniMax: MiniMax M3.1 Flash released?
Google: Gemini 2.5 Flash Lite (batch) was listed on 2025-07-22; MiniMax: MiniMax M3.1 Flash on 2026-10-19.
Gemini 2.5 Flash-Lite is a lightweight reasoning model in the Gemini 2.5 family, optimized for ultra-low latency and cost efficiency. It offers improved throughput, faster token generation, and better performance...
MiniMax-M3.1-Flash is a multimodal model from MiniMax. Compared with M3, it delivers significant improvements across multiple benchmarks, particularly in complex agentic tasks, coding, and cybersecurity. It is built for complex,...