GPT-4 vs Muse Spark 1.3 Contributor
| Signal | GPT-4 | Delta | Muse Spark 1.3 Contributor |
|---|---|---|---|
Capabilities | 50 | -50 | |
Benchmarks | 66 | +66 | |
Pricing | 40 | -60 | |
Context window size | 62 | -33 | |
Recency | 0 | -100 | |
Output Capacity | 58 | -38 | |
| Overall Result | 1 wins | of 6 | 5 wins |
Score History
64.9
current score
GPT-4
right now
40
current score
GPT-4
OpenAI
Muse Spark 1.3 Contributor
meta
Muse Spark 1.3 Contributor saves you $5980.00/month
That's $71760.00/year compared to GPT-4 at your current usage level of 100K calls/month.
| Metric | GPT-4 | Muse Spark 1.3 Contributor | Winner |
|---|---|---|---|
| Overall Score | 65 | 40 | GPT-4 |
| Rank | #197 | #264 | GPT-4 |
| Quality Rank | #197 | #264 | GPT-4 |
| Adoption Rank | #197 | #264 | GPT-4 |
| Parameters | -- | -- | -- |
| Context Window | 8K | 1049K | Muse Spark 1.3 Contributor |
| Pricing | $30.00/$60.00/M | $0.10/$0.20/M | -- |
| Signal Scores | |||
| Capabilities | 50 | 100 | Muse Spark 1.3 Contributor |
| Benchmarks | 66 | -- | GPT-4 |
| Pricing | 40 | 100 | Muse Spark 1.3 Contributor |
| Context window size | 62 | 96 | Muse Spark 1.3 Contributor |
| Recency | 0 | 100 | Muse Spark 1.3 Contributor |
| Output Capacity | 58 | 96 | Muse Spark 1.3 Contributor |
Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.
Scores 65/100 (rank #197), placing it in the top 32% of all 290 models tracked.
Scores 40/100 (rank #264), placing it in the top 9% of all 290 models tracked.
GPT-4 has a 25-point advantage, which typically translates to noticeably stronger performance on complex reasoning, code generation, and multi-step tasks.
Choose GPT-4 when you need:
- Budget-friendly applications with moderate quality requirements
Choose Muse Spark 1.3 Contributor when you need:
- High-volume production workloads where API costs must be minimized
- Processing long documents or large codebases (1049K token context)
- Multimodal workflows that require image understanding
- Step-by-step reasoning and chain-of-thought problem solving
Muse Spark 1.3 Contributor offers 100% better value per quality point. At 1M tokens/day, you'd spend $4.50/month with Muse Spark 1.3 Contributor vs $1350.00/month with GPT-4 - a $1345.50 monthly difference.
Both models have comparable response speeds. For most applications, the latency difference is negligible.
When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. Muse Spark 1.3 Contributor also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (1049K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.20/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (65/100) correlates with better nuance, coherence, and style in long-form content
Image understanding & OCR
Supports vision input - can analyze screenshots, diagrams, photos, and scanned documents directly
GPT-4 clearly outperforms Muse Spark 1.3 Contributor with a significant 24.900000000000006-point lead. For most general use cases, GPT-4 is the stronger choice. However, Muse Spark 1.3 Contributor may still excel in niche scenarios.
By Use Case
Best for Quality
GPT-4
Marginally better benchmark scores; both are excellent
Best for Cost
Muse Spark 1.3 Contributor
100% lower pricing; better value at scale
Best for Reliability
GPT-4
Higher uptime and faster response speeds
Best for Prototyping
GPT-4
Stronger community support and better developer experience
Best for Production
GPT-4
Wider enterprise adoption and proven at scale
by OpenAI
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Reliability - Higher uptime and faster response speeds
- Choose for Prototyping - Stronger community support and better developer experience
- Choose for Production - Wider enterprise adoption and proven at scale
| Capability | GPT-4 | Muse Spark 1.3 Contributor |
|---|---|---|
| Vision (Image Input)differs | ||
| Function Calling | ||
| Streaming | ||
| JSON Mode | ||
| Reasoningdiffers | ||
| Web Searchdiffers | ||
| Image Output |
GPT-4
OpenAI
Muse Spark 1.3 Contributor
meta
Muse Spark 1.3 Contributor saves you $125.58/month
That's 100% cheaper than GPT-4 at 1,000 tokens/request and 100 requests/day.
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | GPT-4 | Muse Spark 1.3 Contributor |
|---|---|---|
| Context Window | 8K | 1.0M |
| Max Output Tokens | 4,096 | 943,718 |
| Open Source | No | No |
| Created | May 28, 2023 | Sep 2, 2026 |