muse-glimmer in fedi-index
The score in every slice, what it is made of, value, local run and history.
fedi-index · General
B 1,365 ±5
Percentile 52 · #142 · provisional
People prefer / Solves tasks
1,376 / —
Human votes vs benchmarks, Elo-eq
Value
—
On your hardware
Closed weights: cloud only.
Score decomposition
B General 1,365 [1,360–1,370] Percentile 52 · #142 · components: 6 provisional
| Source | Component | Value | Elo-eq | Weight | Measured | Variant |
|---|---|---|---|---|---|---|
| LMArena |
text/overall
|
1,389 ±4.92 | 1,390 ±5 | 27.4% | 2026-10-02 | — |
| LMArena |
text/hard_prompts
|
1,397 ±6.08 | 1,392 ±6 | 26.8% | 2026-10-02 | — |
| LMArena |
text/instruction_following
|
1,374 ±8.26 | 1,389 ±8 | 12.0% | 2026-10-02 | — |
| LMArena |
text/expert
|
1,387 ±14 | 1,384 ±12 | 9.4% | 2026-10-02 | — |
| LMArena |
text/longer_query
|
1,382 ±7.40 | 1,384 ±7 | 6.3% | 2026-10-02 | — |
| LMArena |
text/multi_turn
|
1,400 ±12 | 1,399 ±11 | 4.9% | 2026-10-02 | — |
Weight is the share of the component in the score (the rest is the prior that pulls models with little data towards the population median). Methodology
B Coding 1,382 [1,375–1,388] Percentile 58 · #117 · components: 2 provisional
| Source | Component | Value | Elo-eq | Weight | Measured | Variant |
|---|---|---|---|---|---|---|
| LMArena |
webdev/overall
|
1,355 ±7.94 | 1,408 ±2 | 50.0% | 2026-10-01 | — |
| LMArena |
text/coding
|
1,417 ±9.16 | 1,397 ±8 | 39.4% | 2026-10-02 | — |
Weight is the share of the component in the score (the rest is the prior that pulls models with little data towards the population median). Methodology
B Writing 1,359 [1,345–1,373] Percentile 51 · #132 · components: 2 provisional
| Source | Component | Value | Elo-eq | Weight | Measured | Variant |
|---|---|---|---|---|---|---|
| LMArena |
text/creative_writing
|
1,339 ±12 | 1,366 ±12 | 55.0% | 2026-10-02 | — |
| LMArena |
text/longer_query
|
1,382 ±7.40 | 1,384 ±7 | 36.6% | 2026-10-02 | — |
Weight is the share of the component in the score (the rest is the prior that pulls models with little data towards the population median). Methodology
C Language: 繁體中文 1,366 [1,343–1,388] Percentile 43 · #127 · components: 1 provisional
| Source | Component | Value | Elo-eq | Weight | Measured | Variant |
|---|---|---|---|---|---|---|
| LMArena |
text/chinese
|
1,412 ±16 | 1,383 ±13 | 90.3% | 2026-10-02 | — |
Weight is the share of the component in the score (the rest is the prior that pulls models with little data towards the population median). Methodology
B Language: English 1,361 [1,347–1,376] Percentile 50 · #136 · components: 1 provisional
| Source | Component | Value | Elo-eq | Weight | Measured | Variant |
|---|---|---|---|---|---|---|
| LMArena |
text/english
|
1,387 ±7.65 | 1,374 ±8 | 92.5% | 2026-10-02 | — |
Weight is the share of the component in the score (the rest is the prior that pulls models with little data towards the population median). Methodology
C Language: Русский 1,380 [1,357–1,403] Percentile 49 · #119 · components: 1 provisional
| Source | Component | Value | Elo-eq | Weight | Measured | Variant |
|---|---|---|---|---|---|---|
| LMArena |
text/russian
|
1,392 ±15 | 1,400 ±13 | 90.1% | 2026-10-02 | — |
Weight is the share of the component in the score (the rest is the prior that pulls models with little data towards the population median). Methodology
History
The same in a table
| Model | 2026-10 |
|---|---|
| muse-glimmer | 1,365 B |
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