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
Meta: Muse Spark 1.3 Contributor
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$72.50
$11.50
Meta: Muse Spark 1.3 Contributor saves $61.00
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$61.00
$14.00
Meta: Muse Spark 1.3 Contributor saves $47.00
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)
$66.00
$14.40
Meta: Muse Spark 1.3 Contributor saves $51.60
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$39.00
$9.20
Meta: Muse Spark 1.3 Contributor saves $29.80
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$17.50
$5.20
Meta: Muse Spark 1.3 Contributor saves $12.30
Capabilities side by side
Capability
Google: Gemini 2.5 Flash
Meta: Muse Spark 1.3 Contributor
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
✓ Yes
accept documents without your own parsing step
Image output
—
—
generate images, not just text
Built-in web search
✓ Yes
✓ Yes
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.
Price history
Google: Gemini 2.5 Flash: price unchanged since we started tracking it on 2026-03-10.
Meta: Muse Spark 1.3 Contributor: price unchanged since we started tracking it on 2026-09-03.
Which should you choose?
Choose Google: Gemini 2.5 Flash if…
you need audio input — to take speech or audio directly; Meta: Muse Spark 1.3 Contributor does not advertise it
you need seed (reproducible sampling) — to repeat a generation for tests and evals; Meta: Muse Spark 1.3 Contributor does not advertise it
Choose Meta: Muse Spark 1.3 Contributor if…
cost matters at scale — it is 85% cheaper on a typical 3:1 input/output mix ($11.50 vs $72.50 a month for 50,000 support chats)
you generate long outputs in one go — up to 944K tokens (about 707,800 words) per response
you want the newer model — released 2026-09-02, 15 months after the other
Frequently asked questions
Is Google: Gemini 2.5 Flash better than Meta: Muse Spark 1.3 Contributor?
Neither wins outright: Google: Gemini 2.5 Flash is the pick when you need audio input, Meta: Muse Spark 1.3 Contributor when cost matters at scale. In short: Google: Gemini 2.5 Flash when you need audio input, you need seed (reproducible sampling); Meta: Muse Spark 1.3 Contributor when cost matters at scale, you generate long outputs in one go, you want the newer model.
Which is cheaper, Google: Gemini 2.5 Flash or Meta: Muse Spark 1.3 Contributor?
Meta: Muse Spark 1.3 Contributor is cheaper: $0.13 vs $0.85 per 1M tokens at a typical 3:1 input/output mix, 85% less. For 50,000 support conversations a month that is $11.50 against $72.50.
How much do Google: Gemini 2.5 Flash and Meta: Muse Spark 1.3 Contributor cost per million tokens?
Google: Gemini 2.5 Flash costs $0.30 per 1M input tokens and $2.50 per 1M output tokens; Meta: Muse Spark 1.3 Contributor costs $0.10 input and $0.20 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Google: Gemini 2.5 Flash or Meta: Muse Spark 1.3 Contributor?
Both take 1.0M tokens per request — roughly 1,573 pages of text.
Do Google: Gemini 2.5 Flash and Meta: Muse Spark 1.3 Contributor support function calling and JSON output?
Can Google: Gemini 2.5 Flash or Meta: Muse Spark 1.3 Contributor read images?
Yes, both accept image input.
Is Google: Gemini 2.5 Flash or Meta: Muse Spark 1.3 Contributor free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of Google: Gemini 2.5 Flash and Meta: Muse Spark 1.3 Contributor?
Google: Gemini 2.5 Flash can write up to 66K tokens (about 49,200 words) per response; Meta: Muse Spark 1.3 Contributor up to 944K (about 707,800 words).
When were Google: Gemini 2.5 Flash and Meta: Muse Spark 1.3 Contributor released?
Google: Gemini 2.5 Flash was listed on 2025-06-17; Meta: Muse Spark 1.3 Contributor on 2026-09-02.
Gemini 2.5 Flash is Google's state-of-the-art workhorse model, specifically designed for advanced reasoning, coding, mathematics, and scientific tasks. It includes built-in "thinking" capabilities, enabling it to provide responses with greater...
Muse Spark 1.3 Contributor is the cost-efficient contributor tier of Meta’s multimodal reasoning model for experimentation, learning, and early-stage agentic, multi-agent, and coding workflows. It is designed to track information...