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)
inclusionAI: Ling 3.0 Flash VL
Meta: Muse Glimmer 30B
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$8.10
$46.50
inclusionAI: Ling 3.0 Flash VL saves $38.40
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$9.00
$48.00
inclusionAI: Ling 3.0 Flash VL saves $39.00
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)
$9.36
$50.40
inclusionAI: Ling 3.0 Flash VL saves $41.04
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$5.88
$31.20
inclusionAI: Ling 3.0 Flash VL saves $25.32
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$3.18
$16.20
inclusionAI: Ling 3.0 Flash VL saves $13.02
Capabilities side by side
Capability
inclusionAI: Ling 3.0 Flash VL
Meta: Muse Glimmer 30B
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
✓ 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.
cost matters at scale — it is 83% cheaper on a typical 3:1 input/output mix ($8.10 vs $46.50 a month for 50,000 support chats)
you generate long outputs in one go — up to 33K tokens (about 24,600 words) per response
you want to prototype at zero cost — a free variant is listed
Choose Meta: Muse Glimmer 30B if…
No advantage on the data we track — pick it for provider preference or output quality on your own prompts.
Frequently asked questions
Is inclusionAI: Ling 3.0 Flash VL better than Meta: Muse Glimmer 30B?
inclusionAI: Ling 3.0 Flash VL comes out ahead on the data we track: 3 advantages and none for Meta: Muse Glimmer 30B.
Which is cheaper, inclusionAI: Ling 3.0 Flash VL or Meta: Muse Glimmer 30B?
inclusionAI: Ling 3.0 Flash VL is cheaper: $0.09 vs $0.52 per 1M tokens at a typical 3:1 input/output mix, 83% less. For 50,000 support conversations a month that is $8.10 against $46.50.
How much do inclusionAI: Ling 3.0 Flash VL and Meta: Muse Glimmer 30B cost per million tokens?
inclusionAI: Ling 3.0 Flash VL costs $0.06 per 1M input tokens and $0.18 per 1M output tokens; Meta: Muse Glimmer 30B costs $0.30 input and $1.20 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, inclusionAI: Ling 3.0 Flash VL or Meta: Muse Glimmer 30B?
Both take 131K tokens per request — roughly 197 pages of text.
Do inclusionAI: Ling 3.0 Flash VL and Meta: Muse Glimmer 30B support function calling and JSON output?
Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception and advanced visual...
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...