Four frontier AI models now compete for the top spot: GPT-5.4, Claude Opus 4.6, Gemini 3.1 Pro, and Meta’s new Muse Spark. Each one leads in different areas. None is best at everything.
But most comparisons stop at the overall score and miss the details that actually matter when choosing a model for your work. So here’s the breakdown — category by category, with real benchmark numbers.
The Overall Scorecard
Artificial Analysis, an independent AI benchmarking firm, maintains the Intelligence Index — the closest thing we have to a single number that captures model quality. Here’s where things stand as of April 2026:
| Model | Intelligence Index | Coding (Terminal-Bench) | Reasoning (ARC-AGI-2) | Multimodal (MMMU-Pro) | Health (HealthBench Hard) | Price |
|---|---|---|---|---|---|---|
| Gemini 3.1 Pro | 57 | 68.5 | 76.5 | 82.4% | 20.6 | $20/mo |
| GPT-5.4 | 57 | 75.1 | 76.1 | 78.3% | 40.1 | $20/mo |
| Claude Opus 4.6 | 53 | 80.8 (SWE-bench) | 71.2 | 75.8% | 38.5 | $20/mo |
| Muse Spark | 52 | 59.0 | 42.5 | 80.5% | 42.8 | Free |
Tied at the top: GPT-5.4 and Gemini 3.1 Pro share the lead at 57. Claude Opus follows closely at 53. Muse Spark rounds out the top 4 at 52.
But those overall scores hide dramatic differences in specific capabilities. Let’s dig in.
Coding: Claude and GPT Own This Category
If you write code — or use AI to write it for you — the choice is clear.
Claude Opus 4.6 leads on SWE-bench Verified with 80.8%, the benchmark that tests whether a model can actually fix real bugs in real codebases. GPT-5.4 follows at 75.1 on Terminal-Bench. Gemini is solid at 68.5.
Muse Spark? It scores 59.0 on Terminal-Bench. That’s a 16-point gap behind GPT-5.4 and a 21-point gap behind Claude on their respective coding benchmarks.
In practical terms: Muse Spark can write simple scripts and explain code. But for debugging production software, writing tests, refactoring complex systems, or agent-based coding workflows — it’s not competitive. And since there’s no Muse Spark API or IDE integration, you can’t use it in a coding workflow even if you wanted to.
Winner: Claude Opus 4.6 for coding, GPT-5.4 as a strong second. Muse Spark is not in the race.
Reasoning: Gemini and GPT Trade Blows
The ARC-AGI-2 benchmark tests novel pattern recognition — problems a model can’t have seen in training. It’s the closest measure of genuine “thinking” capability.
Gemini 3.1 Pro leads at 76.5. GPT-5.4 is essentially tied at 76.1. Claude scores 71.2 — respectable but trailing.
Muse Spark scores 42.5. Less than half what Gemini achieves. This is the model’s biggest weakness. It handles knowledge-intensive questions well — health, science, history — but when you throw something genuinely novel at it, something that requires abstract logic on unfamiliar patterns, it struggles.
On Humanity’s Last Exam (HLE), which tests harder reasoning with a different methodology, Muse Spark fares better: 39.9% vs GPT-5.4’s 41.6% and Gemini’s 44.7%. Still trailing, but the gap narrows. Muse Spark’s “Contemplating” mode (step-by-step reasoning, similar to chain-of-thought) helps on structured reasoning problems more than pattern-matching ones.
Winner: Gemini 3.1 Pro narrowly, GPT-5.4 right behind. Muse Spark is notably weak here.
Multimodal Understanding: Muse Spark’s Strength
This is where Meta’s model shines. Multimodal = understanding images, charts, screenshots, and visual content alongside text.
On MMMU-Pro, Gemini leads at 82.4%. But Muse Spark is right there at 80.5% — ahead of GPT-5.4 (78.3%) and Claude (75.8%).
On CharXiv Reasoning — which specifically tests chart and data visualization understanding — Muse Spark actually leads everyone at 86.4, beating GPT-5.4 (82.8) and Gemini (80.2).
This makes sense given Meta’s product strategy. Muse Spark powers the AI in Instagram (photo understanding), Ray-Ban glasses (real-world visual recognition), and WhatsApp (image-based queries). Meta optimized for the thing its 3.2 billion users actually do: share and ask about images.
Practical example: snap a photo of a restaurant menu in another language, and Muse Spark is as good as or better than any other model at translating and explaining it. Take a picture of a chart in a presentation, and it’ll interpret the data more accurately than GPT-5.4 or Claude.
Winner: Gemini 3.1 Pro overall on MMMU-Pro, but Muse Spark leads on chart understanding. Both beat GPT and Claude here.
Health and Medical Knowledge: Muse Spark Leads
This was the surprise of the benchmarks. On HealthBench Hard — which tests medical knowledge, clinical reasoning, and health query accuracy — Muse Spark scores 42.8.
GPT-5.4 scores 40.1. Gemini 3.1 Pro scores 20.6. Grok 4.2 scores 20.3.
Muse Spark leads by a clear margin over GPT-5.4 and absolutely dominates Gemini and Grok on health queries. For the billions of people who ask Meta AI health questions on WhatsApp — “is this rash normal?”, “what are the side effects of this medication?”, “my kid has a fever, what should I do?” — this matters enormously.
Of course, no AI model should replace a doctor. But as a first-pass triage tool that helps you decide whether something needs medical attention, Muse Spark gives the most accurate responses.
Winner: Muse Spark, comfortably. GPT-5.4 second.
Token Efficiency: The Hidden Cost Factor
Here’s a detail most comparisons skip: how many tokens does a model burn to answer the same questions?
Muse Spark used 58 million output tokens to complete the full Intelligence Index evaluation. For comparison:
- Gemini 3.1 Pro: ~60M tokens (similar)
- GPT-5.4: 120M tokens (2x more)
- Claude Opus 4.6: 157M tokens (2.7x more)
Fewer tokens for equivalent work means faster responses, lower API costs at scale, and less compute burned. When Meta eventually opens the Muse Spark API, this efficiency advantage could make it very competitive for high-volume applications.
Winner: Muse Spark and Gemini, tied. Claude is the least token-efficient.
Pricing and Availability
| Model | Consumer Access | API Access | Monthly Cost |
|---|---|---|---|
| Muse Spark | meta.ai, WhatsApp, Instagram, FB | Private preview only | Free |
| GPT-5.4 | ChatGPT | OpenAI API | Free (limited) / $20 Plus / $200 Pro |
| Claude Opus 4.6 | claude.ai | Anthropic API | Free (limited) / $20 Pro / $100 Team |
| Gemini 3.1 Pro | gemini.google.com | Google AI Studio | Free (limited) / $20 AI Premium |
Muse Spark’s killer advantage: it’s completely free with no usage limits for consumers. No subscription tier. No waitlist. If you already use WhatsApp or Instagram, you have access right now.
The trade-off: no API means developers can’t build with it. The other three all have robust APIs with programmatic access, function calling, and agent capabilities.
The Quick Decision Matrix
| If you need… | Use this |
|---|---|
| Best coding assistant | Claude Opus 4.6 |
| Best abstract reasoning | Gemini 3.1 Pro or GPT-5.4 |
| Best image/chart understanding | Muse Spark or Gemini 3.1 Pro |
| Best health/medical answers | Muse Spark |
| Best free option | Muse Spark (consumer) or Gemini (limited API) |
| Best for developers/API | GPT-5.4 or Claude Opus 4.6 |
| Best all-rounder (paid) | GPT-5.4 or Gemini 3.1 Pro (tied at 57) |
| Best for agent/automation | Claude (Managed Agents) or GPT-5.4 (Frontier) |
What This Means for You
If you’re a casual AI user: Muse Spark is the best free option available. It scores 52 on the Intelligence Index — just 5 points behind the leaders. For everyday questions, photo understanding, and health queries, it’s genuinely good. And it’s already in the apps you use. Try it at meta.ai or in WhatsApp before paying $20/month for something else.
If you’re a developer: Muse Spark doesn’t serve you yet — no API, no IDE integration, weak coding benchmarks. Stick with Claude for code-heavy work, GPT-5.4 for general development, or Gemini for projects that need the 2M token context window.
If you’re choosing a paid subscription: The $20/month tier at OpenAI, Anthropic, and Google all give you access to their top models. GPT-5.4 and Gemini tie on the overall index at 57. Claude leads on coding. Gemini leads on reasoning and multimodal. Your workflow determines your winner — there’s no universal “best.”
If you’re a business evaluating AI platforms: Watch the API launch. Muse Spark’s token efficiency (58M vs 157M for Claude) could translate to significant cost savings at scale. But until there’s public API access, pricing, and rate limits, it’s not a realistic option for production workloads.
The Bottom Line
There is no single best AI model in April 2026. There are four top-tier options that each dominate different categories:
- Gemini 3.1 Pro: Best reasoning, best multimodal, tied for #1 overall
- GPT-5.4: Best at coding (non-Claude), best all-rounder, tied for #1
- Claude Opus 4.6: Best at coding, best agent infrastructure, close #3
- Muse Spark: Best at health/medical, best free option, best token efficiency, #4 overall
The real question isn’t “which is best?” It’s “which is best for what I need?” And for the first time, one of those top options costs nothing.
Sources:
- Muse Spark: Everything you need to know — Artificial Analysis
- Muse Spark Intelligence & Performance Analysis — Artificial Analysis
- Muse Spark vs GPT-5.4 vs Claude vs Gemini: Full Comparison — Lushbinary
- Meta Muse Spark: Benchmarks, Review & Comparison — BuildFastWithAI
- 5 Things Muse Spark Still Can’t Do Better Than ChatGPT and Claude — Techloy
- Meta is back: Muse Spark and what the benchmarks actually say — What LLM?
- Introducing Muse Spark — Meta AI Blog
- AI Model Benchmarks April 2026 — LM Council
