Models

Muse Spark 1.1 vs Muse Spark 1.2

Compare Muse Spark 1.1 from Meta and Muse Spark 1.2 from Meta on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

MetaMuse Spark 1.1MetaMuse Spark 1.2
Meta logo
Muse Spark 1.1
Meta · text, image, audio, video → text

Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context window.

Input$1.375 /M
Output$4.675 /M
Meta logo
Muse Spark 1.2
Meta · text, image, audio, video → text

Muse Spark 1.1 is a multimodal reasoning model from Meta, built for agentic tasks. It accepts text, images, video, audio, and PDF documents and returns text, with a 1M-token context window.

Input$1.375 /M
Output$4.675 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

Muse Spark 1.1
Muse Spark 1.2
Input /M
$1.375
$1.375
Output /M
$4.675
$4.675
Cache read /M
-
-
Context length
1,000,000
1,000,000
Max output
0
0
Time to First Token
1.9 s
14.2 s
Throughput
125.1 tok/s
108.3 tok/s
Modalities
textimageaudiovideo
textimageaudiovideo
Supported Parameters
thinkingtools
thinkingtools
API Formats
Released
-
-

Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

muse-spark-1.1muse-spark-1.2

Tokens / day

-

Requests / day

-

Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

muse-spark-1.1muse-spark-1.2

Throughput (tok/s)

-

TTFT (s)

-

Uptime (%)

-

LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

Text
muse-spark-1.1muse-spark-1.2
1420146015001540
Overall
14921499
Coding
15311533
Math
14901490
Hard prompts
15111513
Instruction following
14701479
Multi-turn
14941518
Creative writing
14451450
Longer query
14791500
Chinese
15251534
English
14921501
Vision
muse-spark-1.1muse-spark-1.2
12601280130013201340
Overall
12791292
OCR
12921306
Diagram
13041318
Homework
12761276
WebDev Arena
muse-spark-1.1muse-spark-1.2
150015401580
Overall
15341541
React
15291530
HTML
15351544
Gaming
15441569
Simulations
15201553
Data analytics
15161537

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

Muse Spark 1.1
$153 /mo
Muse Spark 1.2
$153 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: Muse Spark 1.1, Muse Spark 1.2?

Muse Spark 1.1: $4.675/M output tokens; Muse Spark 1.2: $4.675/M. Use the cost calculator above to estimate your own workload.

How do their coding arena scores compare?

Muse Spark 1.2: 1533; Muse Spark 1.1: 1531 (LMArena coding leaderboard).

Which responds faster?

Muse Spark 1.1: 1.9s time to first token measured on AIHubMix; see the live performance charts above for how each model behaves across the day.

How large is each context window?

Muse Spark 1.1 accepts 1,000,000 and Muse Spark 1.2 accepts 1,000,000 input tokens.

Which one generates tokens faster?

Muse Spark 1.1 at 125.1 tok/s and Muse Spark 1.2 at 108.3 tok/s, measured as output throughput on AIHubMix — a separate metric from time to first token.

What inputs and capabilities does each model support?

Muse Spark 1.1 accepts text, image, audio and video input and supports thinking and tool calling; Muse Spark 1.2 accepts text, image, audio and video input and supports thinking and tool calling.

Can I call Muse Spark 1.1 and Muse Spark 1.2 with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

Popular comparisons

Related model match-ups readers also look at.