Neither wins outright: Meta: Muse Glimmer 30B (batch) is the pick when cost matters at scale, Qwen: Qwen3 VL 235B A22B Thinking when you need seed (reproducible sampling).
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)
Meta: Muse Glimmer 30B (batch)
Qwen: Qwen3 VL 235B A22B Thinking
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$28.12
$110
Meta: Muse Glimmer 30B (batch) saves $81.88
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$28.50
$88.00
Meta: Muse Glimmer 30B (batch) saves $59.50
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)
$30.00
$96.00
Meta: Muse Glimmer 30B (batch) saves $66.00
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$18.50
$56.00
Meta: Muse Glimmer 30B (batch) saves $37.50
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$9.50
$24.00
Meta: Muse Glimmer 30B (batch) saves $14.50
Capabilities side by side
Capability
Meta: Muse Glimmer 30B (batch)
Qwen: Qwen3 VL 235B A22B Thinking
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
✓ Yes
read token confidence for classification and scoring
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
cost matters at scale — it is 75% cheaper on a typical 3:1 input/output mix ($28.12 vs $110 a month for 50,000 support chats)
you generate long outputs in one go — up to 118K tokens (about 88,500 words) per response
you want the newer model — released 2026-08-09, 11 months after the other
Choose Qwen: Qwen3 VL 235B A22B Thinking if…
you need seed (reproducible sampling) — to repeat a generation for tests and evals; Meta: Muse Glimmer 30B (batch) does not advertise it
Frequently asked questions
Is Meta: Muse Glimmer 30B (batch) better than Qwen: Qwen3 VL 235B A22B Thinking?
Neither wins outright: Meta: Muse Glimmer 30B (batch) is the pick when cost matters at scale, Qwen: Qwen3 VL 235B A22B Thinking when you need seed (reproducible sampling). In short: Meta: Muse Glimmer 30B (batch) when cost matters at scale, you generate long outputs in one go, you want the newer model; Qwen: Qwen3 VL 235B A22B Thinking when you need seed (reproducible sampling).
Which is cheaper, Meta: Muse Glimmer 30B (batch) or Qwen: Qwen3 VL 235B A22B Thinking?
Meta: Muse Glimmer 30B (batch) is cheaper: $0.32 vs $1.30 per 1M tokens at a typical 3:1 input/output mix, 75% less. For 50,000 support conversations a month that is $28.12 against $110.
How much do Meta: Muse Glimmer 30B (batch) and Qwen: Qwen3 VL 235B A22B Thinking cost per million tokens?
Meta: Muse Glimmer 30B (batch) costs $0.17 per 1M input tokens and $0.75 per 1M output tokens; Qwen: Qwen3 VL 235B A22B Thinking costs $0.40 input and $4.00 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Meta: Muse Glimmer 30B (batch) or Qwen: Qwen3 VL 235B A22B Thinking?
Both take 131K tokens per request — roughly 197 pages of text.
Do Meta: Muse Glimmer 30B (batch) and Qwen: Qwen3 VL 235B A22B Thinking support function calling and JSON output?
Can Meta: Muse Glimmer 30B (batch) or Qwen: Qwen3 VL 235B A22B Thinking read images?
Yes, both accept image input.
Is Meta: Muse Glimmer 30B (batch) or Qwen: Qwen3 VL 235B A22B Thinking free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of Meta: Muse Glimmer 30B (batch) and Qwen: Qwen3 VL 235B A22B Thinking?
Meta: Muse Glimmer 30B (batch) can write up to 118K tokens (about 88,500 words) per response; Qwen: Qwen3 VL 235B A22B Thinking up to 33K (about 24,600 words).
When were Meta: Muse Glimmer 30B (batch) and Qwen: Qwen3 VL 235B A22B Thinking released?
Meta: Muse Glimmer 30B (batch) was listed on 2026-08-09; Qwen: Qwen3 VL 235B A22B Thinking on 2025-09-23.
Has the price of Meta: Muse Glimmer 30B (batch) or Qwen: Qwen3 VL 235B A22B Thinking changed?
Muse Glimmer 30B is a dense, open-weight multimodal model from Meta Superintelligence Labs, distilled from Muse Spark and optimized for autonomous agents on consumer hardware. It is suited for long-horizon...
Qwen3-VL-235B-A22B Thinking is a multimodal model that unifies strong text generation with visual understanding across images and video. The Thinking model is optimized for multimodal reasoning in STEM and math....