Muse Spark 1.2 benchmarks & scores
Independent Muse Spark 1.2 AI coding benchmark results Intelligence 57, Coding 74, Agentic 48, with a Vibe Coding Index of 61.6. Compare its overall rank, token price, context window, and practical agentic workflow strengths below.
Evidence confidence
High confidence
Complete core scores supported by at least two current verified sources.
Catalog capabilities
What the model supports
Suite radar
Suite scores
Task placements
Where Muse Spark 1.2 places outside the VCI blend
Head-to-head preference boards that never rewrite the suite scores above — Arena Code WebDev and Design Arena categories only.
Arena Code WebDev
Human preference for web development outputs. Separate from Artificial Analysis coding until blended into the published Coding suite score.
Coding suite score above (73.9, multi-source index) includes this signal when current.
Design Arena categories
Task leaderboards for Muse Spark 1.2
Website, UI, game, data viz, and other tournament boards — not used in the Vibe Coding Index formula.
| Category | Rank | ELO | Win rate | Avg time | Tournaments | |
|---|---|---|---|---|---|---|
|
Web development
|
#6 / 145 | 1,318 | 55.7% | 111.6s | 270 | Full board → |
|
Game development
|
#8 / 133 | 1,322 | 55.9% | 149.7s | 270 | Full board → |
Source record
Tentative Muse Spark 1.2 profile. Artificial Analysis Intelligence Index plus Meta's published launch benchmark suite. Meta ran each model in its own agent product, so cross-model rows are vendor-run rather than harness-identical.
TheVibeFather rankings
Muse Spark 1.2 practical agentic coding scorecard
This is our algorithmic assessment of where Muse Spark 1.2 ranks for common vibe coding and agentic engineering workflows. Every stable 0–10 score is calculated consistently from the sourced Intelligence, Coding, and Agentic signals above—never from an unsourced opinion score.
Small, well-defined code changes
Precision on scoped edits, fixes, and implementation tasks.
UI and CSS iteration
Front-end implementation with iterative tool-driven refinement.
Routine debugging
Diagnosing failures and turning reasoning into correct code changes.
Repository-wide refactors
Coordinating larger edits across files while preserving intent.
Architecture decisions
Reasoning through tradeoffs, constraints, and system-level choices.
Tool use and workflow execution
Planning and completing multi-step work with tools and feedback loops.
Long autonomous coding tasks
Sustaining coherent progress across longer agentic engineering runs.
Overall VibeFather rating
Our complete Vibe Coding Index, expressed on the same 0–10 practical scale.
We start with Intelligence, Coding, Agentic benchmark evidence, and preserve missing values as unverified.
Our code-controlled algorithm blends the native 0–100 signals by workflow and expresses the result on a stable 0–10 scale. Every required input must be present.
Each workflow score is ranked against every model with comparable evidence, so positions update when the benchmark field changes.
The Vibe Coding Index is TheVibeFather’s code-controlled 0–100 composite for practical coding and agentic capability. Price and adoption are reported independently and never alter quality. Exact weighting remains proprietary, inputs, missing-data behavior, and per-category ranks are disclosed here. Read the benchmark methodology →
Recorded score history
How Muse Spark 1.2 has moved
Baseline snapshot recorded.
Where Muse Spark 1.2 sits
Its logo stays full-color and highlighted while the rest of the field recedes for quick comparison.
Vendor key (25)
Alibaba
Amazon
Anthropic
Arcee Ai
Cohere
DeepSeek
Google
Inception
Inclusionai
Kwaipilot
Meta
Meta Llama
MiniMax
Mistral
Moonshot
NVIDIA
Nex Agi
OpenAI
Stepfun
Tencent
Thinkingmachines
Upstage
Xiaomi
Zhipu
xAI
Model benchmark FAQ
Muse Spark 1.2 for vibe coding and agentic engineering
Answers update from this model’s current sourced scores, practical rankings, and verified pricing.
What is Muse Spark 1.2's Vibe Coding Index?
Muse Spark 1.2 has a Vibe Coding Index of 61.6/100 and is #9 of 111 in the current field. The index is TheVibeFather's stable composite for practical AI coding, combining independently sourced Intelligence, Coding, and Agentic benchmark signals. Price and adoption are compared separately and never inflate the quality score.
How does Muse Spark 1.2 rank for vibe coding?
For vibe coding, Muse Spark 1.2's strongest practical area is Small, well-defined code changes at 6.9/10, ranking #10 of 111 models in TheVibeFather rankings.
Is Muse Spark 1.2 good for agentic coding and autonomous tasks?
Muse Spark 1.2 scores 5.5/10 for tool use and workflow execution and 5.0/10 for long autonomous coding tasks. Those categories emphasize the Agentic benchmark signal used for multi-step planning, tool calls, edits, tests, and feedback loops.
What coding benchmark scores does Muse Spark 1.2 have?
The current sourced benchmark profile for Muse Spark 1.2 is Intelligence 57/100, Coding 74/100, Agentic 48/100. TheVibeFather converts those 0–100 signals into consistent practical 0–10 workflow scores so models can be compared for real agentic engineering work.
How much does Muse Spark 1.2 cost for agentic engineering?
The current benchmark uses a 3 to 1 input-to-output blend of $2 per million blended tokens. That places it #81 of 116 by price, where a lower rank number means less expensive.
Are vibe coding, agentic coding, and agentic engineering the same?
They describe overlapping AI-assisted software workflows. Vibe coding emphasizes directing software through intent and iteration, agentic coding emphasizes a model planning and executing multi-step work with tools, agentic engineering is the broader discipline of designing, supervising, and validating those workflows. TheVibeFather benchmarks the shared capabilities behind all three terms on every model page, including Muse Spark 1.2.
