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#128

Muse Glimmer 30B

Meta Release: 2026-08-11 Tested on: 2026-10-01 03:13 meta/muse-glimmer-30b::high
30BDenseOpen source

Summary

Muse Glimmer 30B scores 7.7 on AI BENCHY and ranks #128. It has 10.0 reliability, a 66.7% pass rate, $0.506 total cost, and 69.87s average response time.

Model facts

Researched on 2026-08-12

Reported
Parameters
30B
Architecture
Dense
Availability
Open source
License
Apache-2.0

Score

7.7

Consistency

7.3

Total Cost (Current Price)

$0.506 ↓ -19.1%

Tested at: $0.625

Total Output Tokens

350,370

Total Input Tokens

281,859

Input Price

$0.300 / 1M

Output Price

$1.200 / 1M

Cache Read Price

$0.040 / 1M

Cache Write Price

N/A

Cache prices apply to input tokens. Reads reuse cached prompts; writes store them and can cost extra. Output tokens use the output price.

Tests Correct

Wrong Tests: 12

Attempt pass rate: 66.7%

Flaky tests

8

Flaky tests had mixed outcomes across runs (at least one pass and one fail).

Response Time (avg)

69.87s

Response Time (max): 451.90s

Response Time (total): 1607.12s

Hamster playing table tennis

Prompt: Create a detailed SVG illustration of a hamster playing table tennis.

#128 Muse Glimmer 30B

high
Cost
$0.005
Time
61.7s
Tokens
3,097 tok

Run history

Tested on Score Reliability Tests Correct Total Cost Compare
2026-10-01 03:13 Re-test 7.7 10.0 $0.506 ↓ Current run
2026-08-11 10:10 Initial run 7.3 10.0 $0.529 Compare

This run used a different benchmark suite. Keep suite changes in mind when reading historical movement.

Price History

Historical pricing data for this model from OpenRouter.

Date Input Price Output Price Cache Read Price Cache Write Price
2026-08-14 12:51 $0.350 / 1M $1.500 / 1M N/A N/A
2026-10-06 14:54 $0.300 / 1M $1.200 / 1M $0.040 / 1M N/A

Charts

Choose the first model, then click a second model to open a side-by-side page.

Total Output Tokens

Score vs Total Output Tokens

Quick Compare

Category Breakdown

Category Score Consistency Tests Correct
Agentic 10.0 10.0
Anti-AI Tricks 8.7 7.9
Coding 8.8 7.8
Combined 6.4 5.8
Data parsing and extraction 7.3 5.9
Domain specific 2.9 7.2
General Intelligence 5.3 10.0
Instructions following 8.4 6.9
Puzzle Solving 6.1 4.7
Tool Calling 10.0 10.0
Trivia 3.0 10.0

Compared models