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Model comparison · accepted catalogue facts 2026-10-21

Muse Spark 1.2 vs Kimi K3

Muse Spark 1.2 has an equal-or-higher measured score and an equal-or-lower estimated price. No known model-capability loss from Kimi K3; endpoint and task checks still apply. The reported score intervals overlap; this is not an established quality improvement.

Editorial comparison: Direct benchmark rivals: Muse Spark 1.2 (Meta) vs Kimi K3 (Moonshot AI) with overlapping confidence intervals Inclusion does not recommend either model.

Muse Spark 1.2

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1484.9

Balanced effective USD / 1M tokens · lower is better

$2.00/M

Kimi K3

LMArena general · Elo · higher is better

Scale starts at 1040 Elo

1475.6

Balanced effective USD / 1M tokens · lower is better

$3.05/M

Price under confirmation since Oct 13, 2026

In-Depth Analysis

Muse Spark 1.2 vs Kimi K3: Measured Technical Breakdown

Comprehensive comparison across measured human-preference evaluation, effective production token costs, architectural limits, and migration trade-offs.

Measured Capability (LMArena)
Muse Spark 1.2 leads by 9.3 Elo

Muse Spark 1.2: 1484.9 ±7.38 · Kimi K3: 1475.6 ±4.6 Intervals overlap — not a guaranteed quality advantage

Cost Comparison Across Canonical Production Workloads

Rates represent effective cost per 1M tokens under standard token blends. Cached prompt reads are factored according to workload context reuse.

Workload & RatioMuse Spark 1.2Kimi K3Cost DifferenceAdvantage
Balanced 3 tokens in per 1 out$2.00 /1M tokens$3.05 /1M tokens$1.05 (34% diff)Muse Spark 1.2 costs less
Summarise Huge input, tiny output$1.09 /1M tokens$1.14 /1M tokens$0.056 (5% diff)Muse Spark 1.2 costs less
Chat Long cached system prompt$2.12 /1M tokens$4.38 /1M tokens$2.26 (52% diff)Muse Spark 1.2 costs less
Code gen Output dominates$2.96 /1M tokens$6.28 /1M tokens$3.32 (53% diff)Muse Spark 1.2 costs less
Agentic Context replayed each turn$1.05 /1M tokens$2.01 /1M tokens$0.968 (48% diff)Muse Spark 1.2 costs less

Architectural & Operational Specifications

SpecificationMuse Spark 1.2Kimi K3Operational Note
Context window1,048,576 tokens1,048,576 tokens—
Max output generation943,718 tokens943,718 tokens—
Base input price$1.25 / 1M tokens$0.730 / 1M tokensKimi K3 input rate is cheaper
Base output price$4.25 / 1M tokens$10.00 / 1M tokensMuse Spark 1.2 output rate is cheaper
Cached input price$0.150 / 1M tokens$0.550 / 1M tokensMuse Spark 1.2 offers lower cached prompt cost
Reasoning & thinking tokensSupported; standard ratesSupported; standard rates—
Input modalitiestext, image, video, file, audiotext, image, video—
Tool calling / function useSupportedSupported—
Open weights & licenceProprietary (proprietary)Open weights (kimi-k3)Kimi K3 allows independent hosting or local deployment
Provider & reseller marketMeta · 1 provider offersMoonshot AI · 25 provider offers (4.73× spread)—

When to Choose Muse Spark 1.2

  • Higher measured general capability (1484.9 Elo on human evaluation).
  • Broader multimodal input support: text, image, video, file, audio.
  • Direct integration with Meta tooling and API features.

When to Choose Kimi K3

  • Open weights availability allows private self-hosting and on-premise execution.
  • Direct integration with Moonshot AI tooling and API features.
Risks when moving from Muse Spark 1.2 → Kimi K3:
  • file input is not supported by the candidate.
  • audio input is not supported by the candidate.

Detailed Evidence Passports & Independent Audits

Muse Spark 1.2 Full model card, pricing ladder & provider offers → Kimi K3 Full model card, pricing ladder & provider offers → Alternatives to Muse Spark 1.2 Better-and-cheaper dominance audit → Alternatives to Kimi K3 Better-and-cheaper dominance audit →

Compare · model decision

Choose two or three models

Inspect the differences, estimate your workload and keep the evidence. All standard catalogue models are available, including unrated ones.

Catalogue facts
2026-10-21

2 / 3 selected · 0 requirements
Open public comparison link
Public workload and requirements

These settings are included in the share link. The fixed-request scenario and private evaluation data below are excluded.

A ↔ B

Muse Spark 1.2 has an equal-or-higher measured score and an equal-or-lower estimated price. No known model-capability loss from Kimi K3; endpoint and task checks still apply. The reported score intervals overlap; this is not an established quality improvement.

Estimated blend: 75% input, 25% output; 0% cached input. Base context tier. Prompt length selects the billing tier. An unlisted cache-read rate uses that tier’s full input rate in this blend; missing required input or output rates prevent an estimate. The fixed-request estimate below validates actual context and output limits and requires a published cache-read rate when cache hits are assumed.

What changes between these models

Quality first, then estimated price. LMArena scores are human-preference measurements, not a benchmark of your application. A missing score is unrated.

  • Muse Spark 1.2 · Meets the stated model requirements
  • Kimi K3 · Meets the stated model requirements
Material differences and unknown evidence. Deltas compare each model with model A. Unknown facts remain visible.
Measured factA Muse Spark 1.2B Kimi K3
LMArena general score (Elo)1,484.91,475.6Δ vs A: -9.3 Elo
Score interval half-width (± Elo)7.384.6Δ vs A: -2.78 Elo
Benchmark reasoning effortxhighmax
LMArena document score (Elo)UnknownUnknown
Estimated effective USD / 1M tokens$2$3.0475Δ vs A: +1.0475 USD/M
Base input USD / 1M tokens$1.25$0.73Δ vs A: -0.52 USD/M
Base output USD / 1M tokens$4.25$10Δ vs A: +5.75 USD/M
Base cached-input USD / 1M tokens$0.15$0.55Δ vs A: +0.4 USD/M
Price statusAs of the catalogue dateUnder confirmation since 2026-10-13
Input modalitiestext, image, video, file, audiotext, image, video
Open weightsNot supportedSupportedΔ vs A: +1
Recorded licenceproprietarykimi-k3
Model providerMetaMoonshot AI
Distinct sellers in the catalogue120Δ vs A: +19
Serving precision differs across offersNot supportedSupportedΔ vs A: +1
Recorded retirement dateUnknownUnknown
5 shared measured facts
Shared measured facts. Deltas compare each model with model A. Unknown facts remain visible.
Measured factA Muse Spark 1.2B Kimi K3
Context window (tokens)1,048,5761,048,576Δ vs A: 0 tokens
Output limit (tokens)943,718943,718Δ vs A: 0 tokens
Tool useSupportedSupportedΔ vs A: 0
ReasoningSupportedSupportedΔ vs A: 0
Retirement evidenceNone announced; not a guaranteeNone announced; not a guarantee

Provider counts and precision flags describe catalogue offers. They do not establish the precision, availability, region, tool behaviour or limits of your chosen endpoint. Open each model’s provider table before switching.

Complete price ladders and billing conditions

Muse Spark 1.2

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token thresholdInputOutputCached input
Base, up to and including first threshold$1.25$4.25$0.15

Kimi K3

Rates below are USD per 1M tokens. A threshold selects that whole input/output rate pair.

Input-token thresholdInputOutputCached input
Base, up to and including first threshold$0.73$10$0.55
Migration preflight · compare each candidate with model A

Keeping Muse Spark 1.2 is a valid decision. No pairwise comparison certifies a drop-in replacement.

Muse Spark 1.2 → Kimi K3

Known loss or failed requirement

  • file input is not supported by the candidate.
  • audio input is not supported by the candidate.
  • Provider endpoint, serving precision, availability and task success need your own verification. Catalogue model capabilities do not certify an endpoint.
Check alternatives to Muse Spark 1.2

Estimate a fixed request shape

Private to this tab unless you save locally or explicitly export private details. These are estimates, not observed invoices. Cross-model token counts and task success are assumptions.

0.1 extra attempts means 10 extra full attempts per 100 requests. Cache writes, tool charges, taxes and unlisted charges are excluded.

  • Muse Spark 1.2Estimated total: $4.625 1,000 full attempts · base rates
  • Kimi K3Estimated total: $6.46 1,000 full attempts · base rates
Prompt and output sensitivity · sampled scenarios

Every point recalculates the entire request shape. Tier-boundary samples include one token below, at and above each threshold. Ordering between samples is not guaranteed. Lowest known cost excludes unknown estimates and is not a replacement recommendation.

Vary input; hold output, requests, cache and retries fixed.
Input tokensMuse Spark 1.2Kimi K3Coverage
2,000$4.625Lowest known$6.46All computed
4,096$7.245Lowest known$7.99008All computed
32,768$43.085$28.92064Lowest knownAll computed
131,072$165.965$100.68256Lowest knownAll computed
Vary output; hold input, requests, cache and retries fixed.
Output tokensMuse Spark 1.2Kimi K3
128$3.044$2.74
2,048$11.204$21.94
8,192$37.316$83.38

Bring your observed evaluation results

JSON is parsed locally. Prompts, filenames, individual responses and extra fields are not retained. Import only aggregate measurements for selected models. Task/version labels do not establish that two evaluations used the same dataset.

Expected format
[{"model":"provider/exact-model-id","task":"support-answer","version":"rubric-1","attempts":100,"successes":84,"costUsd":2.4,"latencyMs":950}]

Use the exact catalogue ID. Replace the example values with observed measurements. Omit costUsd or latencyMs when they are unknown. No public score is inferred from these observations.

Keep the decision and its evidence

A portable record retains selected facts, complete tier ladders, public requirements and the publication manifest. It also embeds the full permitted public catalogue to verify the input artifact checksum. Files are larger for this reason (up to 2 MB); local storage is limited to 12 records. Team review is local to this browser; there is no hosted collaboration.

Saving is opt-in and includes private review fields. Shared comparison links never include them. Version 1 Check references remain separate and are not overwritten or guessed into this format.

Saved local decisions · 0

No version 2 decision records are stored in this browser.

Questions this page answers

Is Muse Spark 1.2 a better-and-cheaper replacement for Kimi K3?

Muse Spark 1.2 has an equal-or-higher measured score and an equal-or-lower estimated price. No known model-capability loss from Kimi K3; endpoint and task checks still apply. The reported score intervals overlap; this is not an established quality improvement.

Which model is higher rated: Muse Spark 1.2 or Kimi K3?

Muse Spark 1.2 scores higher on LMArena general (1484.9 ±7.4) compared to Kimi K3 (1475.6 ±4.6), a margin of 9.3 Elo points. However, because the 95% confidence intervals overlap, this does not establish an unconditional superiority across all tasks.

Which model is more cost-effective: Muse Spark 1.2 or Kimi K3?

On a standard balanced workload (3 prompt tokens per 1 generated token), Muse Spark 1.2 costs $2.00 per 1M tokens versus $3.05 (price under confirmation since 2026-10-13) for Kimi K3. Kimi K3 is approximately 1.5× the price of Muse Spark 1.2. Base input rates are $1.25 for Muse Spark 1.2 and $0.730 for Kimi K3; base output rates are $4.25 for Muse Spark 1.2 and $10.00 for Kimi K3.

How do their context windows and generation limits compare?

Both Muse Spark 1.2 and Kimi K3 provide an identical 1,048,576-token context window. Maximum output generation limits are 943,718 tokens for Muse Spark 1.2 and 943,718 tokens for Kimi K3.

What capabilities are lost when switching between Muse Spark 1.2 and Kimi K3?

Switching from Muse Spark 1.2 to Kimi K3 involves: file input is not supported by the candidate; audio input is not supported by the candidate. Run test suites on your specific prompt templates and tool declarations before cutting over production traffic.

Can Muse Spark 1.2 or Kimi K3 be self-hosted or deployed privately?

Kimi K3 provides open weights, enabling self-hosting on private GPU infrastructure, local quantization, and private data pipelines. Managed inference is also offered across third-party API providers (1 for Muse Spark 1.2, 25 for Kimi K3).

What is included in this comparison?

Accepted model capabilities, context and output limits, complete price-tier ladders, independent LMArena measurements and missing evidence. Provider endpoint precision and application success still need verification.

Can I compare a different workload or keep a decision record?

Yes. Change the public workload, prompt length and requirements in the comparison workspace. Fixed-request scenarios, aggregate evaluations and review notes stay local unless explicitly exported.

Evidence & Ask
Markdown for LLMs