Is Muse Spark 1.1 a good deal?

Whether anything in this catalogue beats Muse Spark 1.1 on both quality and price, and what you give up if it does. A computation on the current catalogue, not an opinion.

13 undominated of 136 · Sep 23, 2026

As of Sep 23, 2026, Muse Spark 1.1 is dominated for Balanced on LMArena. Muse Spark 1.3 scores 9.5 higher at the same price, with a covering envelope. 13 of 136 rated, priced standard models are undominated.

Inspect model evidence Compare differences & requirements

Current model

Muse Spark 1.1

Balanced

3 tokens in per 1 out

Muse Spark 1.3 scores 9.5 points higher than Muse Spark 1.1 at the same price, $2.00 per million tokens for both.

Muse Spark 1.1

LMArena Elo · higher is better

Scale starts at 1040 Elo

1480.2

Effective $/M · Balanced · lower is better

$2.00/M

Muse Spark 1.3

LMArena Elo · higher is better

Scale starts at 1040 Elo

1489.7

Effective $/M · Balanced · lower is better

$2.00/M

Muse Spark 1.1 takes text, image, video, file, audio, returns up to 943,718 tokens from a 1,048,576-token context, and is listed by 1 seller.

Compared against 136 rated, priced models on this lens: 1 model dominates it and gives up nothing, 2 more dominate it but give something up. Muse Spark 1.1 scores 1480.2 at $2.00 per million tokens for this mix.

Envelope-safe replacements

Each row scores at least as high, costs no more, and covers this model’s context, output, modalities, tools, and reasoning. A cheaper narrower model is not listed here.

ModelLMArenaEffective $/MYou save
Muse Spark 1.31489.7 +9.5$2.00/M0%

Higher score, lower price, named losses

Not a drop-in. The loss is why these are not a recommendation.

ModelLMArenaEffective $/MYou give up
Gemini 3.8 Flash1494.7$1.50/Mmax output
Gemini 3.7 Flash1490.5$1.50/Mmax output
Muse Spark 1.31489.7 · $2.00/MMuse Spark 1.11480.2 · $2.00/MLMArena EloEffective $/M · Balanced
136 rated, priced standard models. Chartreuse is the frontier. Cobalt is the model you named, when it is not on the staircase.

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Constraint: replacements must preserve the model’s capabilities; any losses remain named trade-offs.

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Evidence & Ask