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Meta: Muse Spark 1.2

Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows.

Source-linked muse Closed weights Released 2026-08-05
API record Report
InputT
OutputT
Input price$1.25/M
Output price$4.25/M
Context1.04858M
Max output131.072K
Providers14
Inference availability

Providers

Provider-specific identifiers, limits, and listed prices per million tokens. Every row links back to the provider's own documentation.

Report a price
Providers offering Muse Spark 1.2
ProviderProvider model IDContextMax outputInputOutputCache readCapabilitiesDocs
OpenCode Go muse-spark-1.2 1.04858M 131.072K $0.1 $0.2 $0.002 ReasoningToolsJSON Docs ↗
DevPass (LLM Gateway) muse-spark-1.2 1.04858M 131.072K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
Kilo Gateway meta/muse-spark-1.2 1.04858M 943.718K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
EmpirioLabs AI muse-spark-1-2 1.04858M 131.072K $1.25 $4.25 $1 ReasoningToolsJSON Docs ↗
Merge Gateway meta/muse-spark-1.2 1.04858M 262.144K $1.25 $4.25 $0.15 ReasoningTools Docs ↗
LLM Gateway meta/muse-spark-1.2 1.04858M 131.072K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
Abacus muse-spark-1.2 1.04858M 131.072K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
Opper meta/muse-spark-1.2 1.04858M 131.072K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
NanoGPT meta/muse-spark-1.2 1M 65.536K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
Meta muse-spark-1.2 1.04858M 131.072K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
Vercel AI Gateway meta/muse-spark-1.2 1.04858M 1.04858M $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
OpenRouter meta/muse-spark-1.2 1.04858M 943.718K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
OpenCode Zen muse-spark-1.2 1.04858M 131.072K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗
OrcaRouter meta/muse-spark-1.2 1.04858M 131.072K $1.25 $4.25 $0.15 ReasoningToolsJSON Docs ↗

Capability badges appear only where the provider catalog explicitly lists support. A blank cell means the source is silent, not that the feature is absent.

Listed rates

Price across providers

Input price per million tokens as published by each provider. Bars are drawn from listed rates only — no traffic weighting, since the catalog observes no requests.

Lowest input $0.1/M

Across 14 priced providers

Median input $1.25/M

Midpoint of listed rates

Highest input $1.25/M

12.5× the lowest listed rate

Output range $0.2 – $4.25

Per million output tokens

OpenCode Go $0.1/MLowest
DevPass (LLM Gateway) $1.25/M
Kilo Gateway $1.25/M
EmpirioLabs AI $1.25/M
Merge Gateway $1.25/M
LLM Gateway $1.25/M
Abacus $1.25/M
Opper $1.25/M
NanoGPT $1.25/M
Meta $1.25/M
Vercel AI Gateway $1.25/M
OpenRouter $1.25/M
OpenCode Zen $1.25/M
OrcaRouter $1.25/M
Cost calculator

Estimate a workload

$0.00
Excludes taxes, non-token charges, and tiered discounts.

Context limits also differ by provider, from 1M to 1.04858M tokens. Compare the provider table above before choosing on price alone.

Specification

Capabilities

Recorded from the source catalog and provider listings.

✓ Reasoning Yes
✓ Tool calling Yes
✓ Structured output Yes
✓ Attachments Yes
✓ Vision input Yes
× Open weights No
Creator
Meta
Model family
muse
Knowledge cutoff
Not documented
License
Not documented
Release date
2026-08-05
Model ID
meta/muse-spark-1.2
Published evaluations

Benchmarks

Every result stays attached to its source, version, metric and harness. Scores from different versions are never merged, and the profile below plots each benchmark against its own population rather than on a shared scale.

Benchmark registry
Benchmark profile
Coding IndexCoding Index Agentic IndexAgentic Index IntelligenceIntelligence Index Design Arena: w…Design Arena: website Design Arena: c…Design Arena: codecategories Design Arena: g…Design Arena: gamedev Design Arena: d…Design Arena: dataviz Design Arena: u…Design Arena: uicomponent This model — Coding Index: 72.2 index (86.1th percentile) This model — Agentic Index: 44 index (86.3th percentile) This model — Intelligence Index: 39.8 index (78.9th percentile) This model — Design Arena: website: 1322 elo (97.4th percentile) This model — Design Arena: codecategories: 1326 elo (93.7th percentile) This model — Design Arena: gamedev: 1323 elo (88.6th percentile) This model — Design Arena: dataviz: 1354 elo (95.5th percentile) This model — Design Arena: uicomponent: 1332 elo (91.0th percentile)

Each axis is this model's percentile among the 8 benchmarks it has published results for, measured against every other model with a score on that same benchmark. Percentiles are used because benchmarks do not share a scale — a 60 on one is not a 60 on another. Hover any point for the raw score.

Coding Index index Source ↗
Coding Index #29 of 205
Agentic Index index Source ↗
Agentic Index #27 of 193
Intelligence Index index Source ↗
Intelligence Index #41 of 192
Design Arena: website elo Source ↗
Design Arena: website #4 of 175
Design Arena: codecategories elo Source ↗
Design Arena: codecategories #10 of 167
Design Arena: gamedev elo Source ↗
Design Arena: gamedev #19 of 166
Design Arena: dataviz elo Source ↗
Design Arena: dataviz #8 of 165
Design Arena: uicomponent elo Source ↗
Design Arena: uicomponent #15 of 161
Design Arena: 3d elo Source ↗
Design Arena: 3d #21 of 157
Design Arena: svg elo Source ↗
Design Arena: svg #9 of 116
Design Arena: asciiart elo Source ↗
Design Arena: asciiart #7 of 99
Design Arena: fullstack elo Source ↗
Design Arena: fullstack #26 of 67
Design Arena: webapps elo Source ↗
Design Arena: webapps #18 of 67
Design Arena: mobileapps elo Source ↗
Design Arena: mobileapps #33 of 66
Design Arena: androidnative elo Source ↗
Design Arena: androidnative #18 of 59
Design Arena: python-pptxslides elo Source ↗
Design Arena: python-pptxslides #27 of 47
Design Arena: agenticgamedev elo Source ↗
Design Arena: agenticgamedev #27 of 44
Design Arena: htmlslides elo Source ↗
Design Arena: htmlslides #35 of 40

Each strip shows every published score for that benchmark, with this model marked. The lighter shape behind the ticks is the density of results, and the dashed line is the median.

Cost against capability

Price and performance

Listed input price plotted against Coding Index, the benchmark with the widest published coverage that this model appears in.

0 43 86 $0.01 $0.1 $1 $10 Qwen: Qwen3.6 Plus — $0.325/M, score 54.5 Qwen: Qwen3 Next 80B A3B Thinking — $0.15/M, score 17.4 OpenAI: GPT-4 Turbo (batch) — $5/M, score 21.5 Mistral: Ministral 3 8B 2512 (batch) — $0.075/M, score 9.7 OpenAI: o3 Mini High (batch) — $0.55/M, score 16.3 Qwen: Qwen3.8 Max (0902) — $2/M, score 71.8 Gemini 3.5 Flash — $1.5/M, score 70.1 Z.ai: GLM 5.3 Flash (batch) — $0.075/M, score 71.5 Gemma 3 12B IT — $0.05/M, score 5.8 GPT-4.1 mini — $0.4/M, score 20.2 DeepSeek V4 Pro — $0.435/M, score 59.4 Claude Sonnet 5 — $2/M, score 71.5 Mistral: Ministral 3 8B 2512 — $0.15/M, score 9.7 Gemini 3.1 Flash Lite Preview — $0.25/M, score 34.7 OpenAI: o1 (batch) — $7.5/M, score 39.7 Anthropic: Claude Fable 5.1 (batch) — $5/M, score 81.6 Gemini 3.7 Flash — $0.75/M, score 76.1 LongCat-2.0 — $0.3/M, score 45.3 Z.ai: GLM 5.1 — $0.966/M, score 55.8 Anthropic: Claude Opus 4.8 (batch) — $2.5/M, score 74.3 Mistral: Mistral Large 3 2512 — $0.5/M, score 20.1 DeepSeek V3.2 — $0.18/M, score 44.2 Anthropic: Claude Opus 4.7 — $5/M, score 73.6 Google: Gemini 3.5 Flash (batch) — $0.75/M, score 70.1 OpenAI: GPT-5.4 Nano (batch) — $0.1/M, score 56.1 Inception: Mercury 2 — $0.25/M, score 31.1 OpenAI: GPT-4o-mini (batch) — $0.075/M, score 11.4 Qwen: Qwen3.5-9B (batch) — $0.17/M, score 28.7 Gemini 3.6 Flash — $0.75/M, score 69.2 Gemma 4 26B A4B IT — $0.042/M, score 39.3 Claude Fable 5 — $10/M, score 76.5 Gemma 4 31B IT — $0.09/M, score 43.4 Z.ai: GLM 5.3 Flash — $0.15/M, score 71.5 OpenAI: GPT-3.5 Turbo (batch) — $0.25/M, score 10.7 Gemma 3 27B IT — $0.08/M, score 10.1 MiniMax: MiniMax M3 — $0.3/M, score 58.6 DeepSeek: DeepSeek V4 Pro 0813 (batch) — $0.66/M, score 68.8 Thinking Machines: Inkling Small (batch) — $0.5/M, score 52.9 Anthropic: Claude Fable 5.1 — $10/M, score 81.6 Google: Gemma 4 31B (batch) — $0.39/M, score 43.4 Qwen: Qwen3.8 2.4T A95B (batch) — $2/M, score 71.9 Mistral: Devstral 2 2512 — $0.4/M, score 31.3 MoonshotAI: Kimi K2.7 Code (batch) — $0.95/M, score 60.8 Inkling — $1.87/M, score 52.1 OpenAI: gpt-oss-20b (batch) — $0.05/M, score 20.7 Muse Spark 1.1 — $1.25/M, score 71.3 MiMo-V2.5 — $0.14/M, score 56.8 Google: Gemini 3.5 Flash Lite (batch) — $0.15/M, score 49.3 Kimi K2 Thinking — $0.4/M, score 21.0 Mistral: Mistral Medium 3.5 (batch) — $0.75/M, score 46.9 GPT-5.6 Luna — $0.2/M, score 71.4 Qwen: Qwen3.8 Max (0803) — $2/M, score 68.9 Mistral: Mistral Medium 3.1 (batch) — $0.2/M, score 20.5 GPT-5.1 — $1.25/M, score 49.4 Qwen: Qwen3.8 27B — $0.42/M, score 68.1 Google: Gemini 3.8 Flash (batch) — $0.375/M, score 76.3 Google: Gemini 3.7 Flash (batch) — $0.375/M, score 76.1 Mistral: Mistral Small 4 (batch) — $0.075/M, score 26.6 inclusionAI: Ling 3.0 Flash VL — $0.06/M, score 57.0 Z.ai: GLM 5.3 (batch) — $0.7/M, score 74.8 DeepSeek: DeepSeek V4 Flash 0731 (batch) — $0.11/M, score 69.1 OpenAI: GPT-5.5 (batch) — $2.5/M, score 74.9 MoonshotAI: Kimi K3 (batch) — $3/M, score 76.2 Inkling Small — $0.45/M, score 52.9 Anthropic: Claude Sonnet 5 (batch) — $1/M, score 71.5 Anthropic: Claude Fable 5 (batch) — $5/M, score 76.5 Nemotron 3 Super 120B A12B — $0.2/M, score 37.7 IBM: Granite 4.2 8B — $0.06/M, score 22.4 OpenAI: GPT-5 (batch) — $0.625/M, score 37.8 Google: Gemini 2.5 Pro (batch) — $0.625/M, score 33.3 GPT OSS 120B — $0.03/M, score 30.4 OpenAI: gpt-oss-120b (batch) — $0.15/M, score 30.4 OpenAI: GPT-4.1 Mini (batch) — $0.2/M, score 20.2 OpenAI: GPT-4.1 Nano (batch) — $0.05/M, score 11.1 SpaceXAI: Grok 4.6 — $2/M, score 76.8 DeepSeek-R1 — $0.7/M, score 24.6 DeepSeek: DeepSeek V3.1 Terminus — $0.27/M, score 43.5 OpenAI: GPT-6 Astra (batch) — $5/M, score 76.9 OpenAI: GPT-5.6 Terra (batch) — $1/M, score 76.7 Gemini 3.1 Pro Preview — $2/M, score 68.8 Gemma 3 4B IT — $0.04/M, score 2.7 DeepSeek V4 Pro 0813 — $0.442/M, score 68.8 Z.ai: GLM 5.2 (batch) — $0.7/M, score 68.8 Google: Gemini 3.6 Flash (batch) — $0.375/M, score 69.2 GPT-6 Astra — $10/M, score 76.9 Nemotron 3 Nano 30B A3B — $0.05/M, score 14.4 Z.ai: GLM 5.3 — $1.4/M, score 74.8 Anthropic: Claude Opus 4.8 — $5/M, score 74.3 SpaceXAI: Grok 4.3 — $1.25/M, score 42.2 GPT-5.6 Terra — $2/M, score 76.7 MiniMax: MiniMax M3 (batch) — $0.3/M, score 58.6 Gemini 3.8 Flash — $0.75/M, score 76.3 NVIDIA: Nemotron 3 Ultra (batch) — $0.6/M, score 49.3 MiniMax: MiniMax M2.7 — $0.3/M, score 52.6 Kimi K2.6 — $0.95/M, score 61.8 Kimi K3 — $3/M, score 76.2 Anthropic: Claude Sonnet 4.5 (batch) — $1.5/M, score 52.1 Claude Opus 5 — $5/M, score 78.0 Claude Opus 5 (batch) — $2.5/M, score 78.0 SpaceXAI: Grok 4.5 — $2/M, score 72.4 Mistral: Mistral Large 3 2512 (batch) — $0.25/M, score 20.1 OpenAI: GPT-5.1 (batch) — $0.625/M, score 49.4 Anthropic: Claude Opus 4.7 (batch) — $2.5/M, score 73.6 Anthropic: Claude Sonnet 4.5 — $3/M, score 52.1 Google: Gemini 3.1 Pro Preview (batch) — $1/M, score 68.8 Mistral: Mistral Medium 3.1 — $0.4/M, score 20.5 MiMo-V2.5-Pro — $0.435/M, score 60.2 Thinking Machines: Inkling (batch) — $1/M, score 52.1 GPT-5.5 — $5/M, score 74.9 OpenAI: GPT-5.4 (batch) — $1.25/M, score 71.1 Anthropic: Claude Sonnet 4.6 — $3/M, score 63.0 Anthropic: Claude Sonnet 4.6 (batch) — $1.5/M, score 63.0 DeepSeek V4 Flash 0731 — $0.05/M, score 69.1 GPT-5 — $1.25/M, score 37.8 Anthropic: Claude Haiku 4.5 (batch) — $0.5/M, score 43.9 OpenAI: GPT-5 Mini (batch) — $0.125/M, score 15.6 Gemini 2.5 Pro — $1.25/M, score 33.3 inclusionAI: Ling 3.0 Flash — $0.021/M, score 50.6 Qwen: Qwen3.7 Plus — $0.32/M, score 55.9 SpaceXAI: Grok 4.3 (batch) — $1/M, score 42.2 Nemotron 3 Ultra 550B A55B — $0.5/M, score 49.3 Anthropic: Claude Sonnet 4 — $3/M, score 37.6 OpenAI: GPT-5.6 Luna (batch) — $0.1/M, score 71.4 OpenAI: GPT-5.4 Mini (batch) — $0.375/M, score 56.1 GPT OSS 20B — $0.02/M, score 20.7 Qwen: Qwen3.8 2.4T A95B — $2/M, score 71.9 GPT-4 Turbo — $10/M, score 21.5 OpenAI: GPT-5.6 Sol (batch) — $1/M, score 77.4 o1 — $15/M, score 39.7 GPT-5.4 mini — $0.75/M, score 56.1 Z.ai: GLM 4.6 — $0.43/M, score 45.8 GPT-5 Mini — $0.25/M, score 15.6 GPT-4 — $30/M, score 13.1 Kimi K2.7 Code — $0.95/M, score 60.8 GPT-4o (2024-05-13) — $5/M, score 24.2 Gemini 3.5 Flash Lite — $0.3/M, score 49.3 Hy3 preview — $0.066/M, score 58.8 Muse Spark 1.2 — $1.25/M, score 72.2 DeepSeek V4 Flash — $0.15/M, score 52.0 Nemotron 3.5 Lightning 30B A3B — $0.05/M, score 26.8 GPT-5.6 Sol — $4/M, score 77.4 GPT-4.1 nano — $0.1/M, score 11.1 GPT-5.4 — $2.5/M, score 71.1 GPT-4o mini — $0.15/M, score 11.4 GPT-5.4 nano — $0.2/M, score 56.1 GPT-3.5-turbo — $0.5/M, score 10.7 Solar Pro 4 — $0.3/M, score 52.7 Kimi K2.5 — $0.3/M, score 46.8 Trinity Large Thinking — $0.25/M, score 25.8 Qwen: Qwen3 30B A3B Thinking 2507 — $0.2/M, score 12.1 Z.ai: GLM 5.2 — $0.966/M, score 68.8 Qwen: Qwen3.7 Max — $1.475/M, score 66.0 SpaceXAI: Grok Build 0.1 — $1/M, score 51.5 Qwen: Qwen3.6 35B A3B — $0.1/M, score 41.9 Qwen: Qwen3.6 27B — $0.3/M, score 53.7 inclusionAI: Ling-2.6-flash — $0.01/M, score 25.3 Mistral: Mistral Small 4 — $0.15/M, score 26.6 Kwaipilot: KAT-Coder-Pro V2 — $0.3/M, score 59.5 Qwen: Qwen3.5-9B — $0.1/M, score 28.7 Qwen: Qwen3.5-35B-A3B — $0.312/M, score 37.0 Qwen: Qwen3.5-122B-A10B — $0.26/M, score 45.7 Upstage: Solar Pro 3 — $0.15/M, score 16.2 Z.ai: GLM 4.7 — $0.4/M, score 45.3 Amazon: Nova 2 Lite — $0.3/M, score 23.0 Mistral: Ministral 3 3B 2512 — $0.1/M, score 4.8 Google: Gemma 3n 4B — $0.06/M, score 3.2 Meta: Llama 4 Maverick — $0.2/M, score 16.3 OpenAI: o3 Mini High — $1.1/M, score 16.3 Meta: Llama 3.3 70B Instruct — $0.1/M, score 11.9 Meta: Llama 3.1 8B Instruct — $0.05/M, score 5.4 Nex AGI: Nex-N2-Pro — $0.25/M, score 59.1 Mistral: Mistral Medium 3.5 — $1.5/M, score 46.9 inclusionAI: Ring-2.6-1T — $0.075/M, score 42.8 IBM: Granite 4.1 8B — $0.05/M, score 9.5 Qwen: Qwen3.5 397B A17B — $0.55/M, score 48.2 Qwen: Qwen3 Coder Next — $0.12/M, score 36.2 Mistral: Ministral 3 14B 2512 — $0.2/M, score 14.4 Anthropic: Claude Haiku 4.5 — $1/M, score 43.9 Qwen: Qwen3 235B A22B Thinking 2507 — $0.23/M, score 22.1 Qwen: Qwen3 8B — $0.117/M, score 9.0 Qwen: Qwen3 14B — $0.227/M, score 13.8 Qwen: Qwen3 32B — $0.08/M, score 15.3 Meta: Llama 4 Scout — $0.1/M, score 8.2 DeepSeek: DeepSeek V3 0324 — $0.25/M, score 21.2 Cohere: Command A — $2.5/M, score 27.8 Step 3.7 Flash — $0.185/M, score 39.6 Muse Spark 1.2 Input price per million tokens (log scale) Index

The stepped line is the efficient frontier: at each price, the best score available for that money or less. A model sitting on it is not being beaten by anything cheaper. Price is log-scaled because listed rates span four orders of magnitude. Only models with both a listed price and a score on this benchmark can appear.

Catalog activity

Change log

Field-level changes detected between successful source imports.

Full change log
Max Output Tokens943718 → 131072
Max Output Tokens131072 → 943718
Max Output Tokens943718 → 131072
Max Output Tokens131072 → 943718
Max Output Tokens943718 → 131072
Max Output Tokens131072 → 943718
Max Output Tokens943718 → 131072
Max Output Tokens131072 → 943718
Max Output Tokens943718 → 131072
Max Output Tokens131072 → 943718
Provenance

Sources & verification

Every figure on this page traces back to one of these records.

Methodology
Last verified
Sep 11, 2026
Status
Source-linked
Confidence
Medium
Catalog source
Models.dev
Models.devcatalog ↗OpenCode Zen documentationprovider documentation ↗LLM Gateway documentationprovider documentation ↗Kilo Gateway documentationprovider documentation ↗EmpirioLabs AI documentationprovider documentation ↗Merge Gateway documentationprovider documentation ↗Abacus documentationprovider documentation ↗Opper documentationprovider documentation ↗NanoGPT documentationprovider documentation ↗Meta documentationprovider documentation ↗Vercel AI Gateway documentationprovider documentation ↗OpenRouter documentationprovider documentation ↗
Public API

Use this record

Fetch the complete source-linked model record. No key, no account, no rate-limited tier.

API documentation
Endpoint
GET https://model.kyssta.lol/api/v1/models/meta/muse-spark-1.2
curl
curl "https://model.kyssta.lol/api/v1/models/meta/muse-spark-1.2"
Common questions

Frequently asked questions

Answered directly from the stored record — nothing here is generated beyond the catalog's own fields.

What is Muse Spark 1.2?

Muse Spark 1.2 is a coding-focused update to Muse Spark 1.1 with improvements in code generation, complex debugging, codebase understanding, and end-to-end developer workflows. It is published by Meta and catalogued here from Models.dev.

How much does Muse Spark 1.2 cost?

Listed input pricing starts at $0.1 per million tokens from OpenCode Go, rising to $1.25 across 14 listed providers.

What is the context length of Muse Spark 1.2?

Muse Spark 1.2 accepts up to 1.04858M tokens of context and returns up to 131.072K output tokens.

Does Muse Spark 1.2 support tool calling and structured output?

Provider catalogs list support for tool calling, structured output, reasoning, and image input.

Which providers serve Muse Spark 1.2?

14 providers list this model: OpenCode Go, DevPass (LLM Gateway), Kilo Gateway, EmpirioLabs AI, Merge Gateway, LLM Gateway and 8 more.

Are the weights for Muse Spark 1.2 open?

No. This model is served through hosted APIs only.

When was Muse Spark 1.2 released?

The catalog records a release date of 2026-08-05, last verified Sep 11, 2026.

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