The best AI model depends on your use case. We compare GPT-5.4, Claude Opus 4.6, and Gemini 3.1 Pro across coding, writing, reasoning, multimodal, price, and speed using current benchmark data.
Share This Report
Copy the link, post it, or save a PDF version.
The best AI model depends on your use case. GPT-5.4 leads on coding and long-context reasoning, Claude Opus 4.6 wins on math and writing quality, and Gemini 3.1 Pro offers the strongest agentic performance at the lowest price. Here's how they compare across every major benchmark category.
| Category | GPT-5.4 | Claude Opus 4.6 | Gemini 3.1 Pro | Winner |
|---|---|---|---|---|
| Overall Score | 84 | 81 | 83 | GPT-5.4 |
| Coding | SWE-bench 84, LCB 84 | SWE-bench 80.8, LCB 76 | SWE-bench 75, LCB 71 | GPT-5.4 |
| Math | AIME '25: 99, BRUMO: 97 | AIME '25: 98, BRUMO: 96 | AIME '25: 99, BRUMO: 96 | Tie (GPT / Gemini) |
| Reasoning | ARC-AGI2 73.3, MuSR 94 | ARC-AGI2 68.8, MuSR 93 | ARC-AGI2 77.1, MuSR 93 | Gemini 3.1 Pro |
| Agentic | TB2 75.1, BC 82.7 | TB2 65.4, BC 84 | TB2 77, BC 86 | Gemini 3.1 Pro |
| Multimodal | MMMU-Pro 81.2, OQA 96 | MMMU-Pro 77.3, OQA 94 | MMMU-Pro 95, OQA 95 | Gemini 3.1 Pro |
| Knowledge | HLE 48, GPQA 92.8 | HLE 53, GPQA 91.3 | HLE 40, GPQA 97 | Mixed |
| Speed | Reasoning (slower) | Non-reasoning (faster) | Non-reasoning (faster) | Claude / Gemini |
| Price (in/out) | $2.50 / $15 | $15 / $75 | $1.25 / $5 | Gemini 3.1 Pro |
| Context Window | 1.05M | 1M | 1M | All comparable |
All three are frontier models. The overall scores — 84, 83, 81 — are close enough that the winner for your workflow depends on which categories matter most to you.
GPT-5.4 is OpenAI's current flagship and the top-ranked model on BenchLM's overall leaderboard at 84. It uses chain-of-thought reasoning at inference time, which adds latency but helps on the hardest problems.
Coding. GPT-5.4 leads both SWE-bench Verified (84) and LiveCodeBench (84). On BenchLM's weighted coding score, it sits at the top of the coding leaderboard. The combination of strong SWE-bench and LiveCodeBench performance means it handles both real repository engineering and fresh algorithmic problems well.
Long-context reasoning. GPT-5.4 scores 95 on LongBench v2 and 97 on MRCRv2, both best-in-class. With a 1.05M-token context window, it can process large codebases and long documents while maintaining accuracy at depth.
Knowledge. 92.8 on GPQA, 93 on MMLU-Pro, and 97 on SimpleQA. GPT-5.4 is the strongest model for factual recall and expert-level question answering, particularly in scientific domains.
Price. At $2.50 / $15 per million tokens, GPT-5.4 is mid-range. Not as expensive as Claude Opus 4.6, but 2x the cost of Gemini 3.1 Pro for input and 3x for output.
Latency. As a reasoning model, GPT-5.4 thinks before it responds. For real-time applications like chat UX, autocomplete, or iterative writing, this delay is noticeable compared to non-reasoning alternatives.
Agentic. Despite strong coding scores, GPT-5.4 trails Gemini 3.1 Pro on agentic benchmarks — 75.1 vs 77 on Terminal-Bench 2.0 and 82.7 vs 86 on BrowseComp.
Claude Opus 4.6 is Anthropic's flagship with an overall score of 81. It is a non-reasoning model — no chain-of-thought at inference time — which makes it noticeably faster for interactive work.
Math. Claude Opus 4.6 scores 98–99 across AIME 2023–2025 and 95–97 on HMMT. While GPT-5.4 matches it on AIME, Claude's consistency across competition math benchmarks is remarkable for a non-reasoning model.
Writing quality. Claude is widely preferred for long-form writing, editing, and creative work. Its non-reasoning architecture produces more natural, flowing responses without the step-by-step feel that reasoning models sometimes have.
Speed. No chain-of-thought overhead means faster time-to-first-token and lower latency per response. For chatbots, drafting tools, and coding assistants where responsiveness matters, this is a real advantage.
Knowledge depth. Claude leads on HLE (Humanity's Last Exam) at 53 vs GPT-5.4's 48 and Gemini's 40. This is the hardest knowledge benchmark available, designed to test the frontier of what models can reason about.
Price. Claude Opus 4.6 is the most expensive of the three at $15 / $75 per million tokens — 6x GPT-5.4 on input and 5x on output. For high-volume API usage, this adds up fast.
Coding. Competitive but not leading. SWE-bench Verified at 80.8 and LiveCodeBench at 76 are strong, but GPT-5.4 has a clear edge on both. See Claude Opus 4.6 vs GPT-5.4 for the full coding breakdown.
Agentic. Terminal-Bench 2.0 at 65.4 is the weakest of the three flagships. Claude is better suited for single-turn and multi-turn chat than for autonomous agent loops.
Gemini 3.1 Pro is Google's current flagship at 83 overall — just one point behind GPT-5.4 and two points ahead of Claude Opus 4.6. It is a non-reasoning model with the best price-to-performance ratio in the frontier tier.
Agentic work. Gemini 3.1 Pro leads on Terminal-Bench 2.0 (77) and BrowseComp (86), making it the strongest model for autonomous agents, browser automation, and tool-use workflows.
Multimodal. 95 on MMMU-Pro — the highest of the three flagships — plus 95 on OfficeQA-Pro. Gemini handles images, documents, and mixed-media inputs better than both competitors.
Reasoning. Gemini leads on ARC-AGI2 at 77.1, ahead of GPT-5.4 (73.3) and Claude Opus 4.6 (68.8). This benchmark tests novel reasoning ability, and Gemini's edge here is significant.
Price. $1.25 / $5 per million tokens. That is half the cost of GPT-5.4 and 12x cheaper than Claude Opus 4.6 on input. For API-heavy applications, Gemini delivers frontier performance at mid-tier pricing.
Coding. SWE-bench Verified at 75 and LiveCodeBench at 71 are the weakest of the three flagships. For dedicated coding workflows, GPT-5.4 or Claude Opus 4.6 are stronger choices.
Knowledge. HLE at 40 is notably lower than Claude's 53 and GPT-5.4's 48. On the hardest expert-level questions, Gemini trails meaningfully.
| Benchmark | GPT-5.4 | Claude Opus 4.6 | Gemini 3.1 Pro |
|---|---|---|---|
| SWE-bench Verified | 84 | 80.8 | 75 |
| SWE-bench Pro | 57.7 | 74 | 72 |
| LiveCodeBench | 84 | 76 | 71 |
| HumanEval | 95 | 91 | 91 |
GPT-5.4 wins on SWE-bench Verified and LiveCodeBench. Claude Opus 4.6 has an interesting lead on SWE-bench Pro at 74 — significantly higher than GPT-5.4's 57.7 — which suggests Claude handles complex multi-file engineering tasks better than the headline numbers might suggest.
Full coding rankings: Best LLMs for Coding.
| Benchmark | GPT-5.4 | Claude Opus 4.6 | Gemini 3.1 Pro |
|---|---|---|---|
| GPQA | 92.8 | 91.3 | 97 |
| MMLU-Pro | 93 | 82 | 92 |
| HLE | 48 | 53 | 40 |
| SimpleQA | 97 | 72 | 95 |
| MuSR | 94 | 93 | 93 |
| LongBench v2 | 95 | 92 | 93 |
Knowledge is the most mixed category. Gemini leads GPQA (97), GPT-5.4 leads SimpleQA (97) and LongBench v2 (95), and Claude leads HLE (53). No single model dominates.
| Benchmark | GPT-5.4 | Claude Opus 4.6 | Gemini 3.1 Pro |
|---|---|---|---|
| Terminal-Bench 2.0 | 75.1 | 65.4 | 77 |
| BrowseComp | 82.7 | 84 | 86 |
| OSWorld-Verified | 75 | 74 | 68 |
| MMMU-Pro | 81.2 | 77.3 | 95 |
| OfficeQA-Pro | 96 | 94 | 95 |
Gemini 3.1 Pro is the clear agentic and multimodal leader. Its 95 on MMMU-Pro is 14 points ahead of GPT-5.4 and 18 ahead of Claude. For workflows that involve browsing, tool use, or visual understanding, Gemini has a structural advantage.
| Model | Input (per 1M tokens) | Output (per 1M tokens) | Context Window |
|---|---|---|---|
| GPT-5.4 | $2.50 | $15.00 | 1.05M |
| Claude Opus 4.6 | $15.00 | $75.00 | 1M |
| Gemini 3.1 Pro | $1.25 | $5.00 | 1M |
For 1 million input tokens and 200K output tokens, the cost is:
Claude Opus 4.6 is 13x more expensive than Gemini 3.1 Pro for the same workload. If cost is a primary constraint, Gemini is the obvious choice at the frontier tier.
All three providers offer cheaper models that are still capable:
| Model | Score | Input | Output |
|---|---|---|---|
| Claude Sonnet 4.6 | 76 | $3.00 | $15.00 |
| Claude Haiku 4.5 | 62 | $0.80 | $4.00 |
| Gemini 2.5 Flash | 50 | $0.15 | $0.60 |
Claude Sonnet 4.6 is a strong mid-range option at 76 overall — it matches or beats GPT-4o (56) and Gemini 2.5 Pro (65) while costing less than GPT-5.4.
The 2026 AI landscape is genuinely three-way competitive. GPT-5.4 (84), Gemini 3.1 Pro (83), and Claude Opus 4.6 (81) are all frontier-class models with distinct strengths. The gap between them is small enough that the right choice depends on your specific use case, not a universal ranking.
For most developers, the decision comes down to: coding (GPT-5.4), agents and value (Gemini 3.1 Pro), or writing and speed (Claude Opus 4.6).
→ Full leaderboard · Compare any two models · Coding leaderboard · Agentic leaderboard
Is ChatGPT better than Claude in 2026? GPT-5.4 leads Claude Opus 4.6 on BenchLM's overall score, 84 to 81. GPT-5.4 is stronger on coding, agentic tasks, and long-context reasoning. Claude leads on math, writing quality, and HLE, and has lower latency as a non-reasoning model.
Is Gemini better than ChatGPT or Claude? Gemini 3.1 Pro scores 83 overall, placing it between GPT-5.4 (84) and Claude Opus 4.6 (81). Gemini leads on agentic benchmarks, multimodal understanding, and offers the best price-to-performance ratio at $1.25 / $5 per million tokens.
Which AI is best for coding in 2026? GPT-5.4 leads BenchLM's coding leaderboard with 84 on both SWE-bench Verified and LiveCodeBench. Claude Opus 4.6 is second, and Gemini 3.1 Pro is third. See the full coding comparison.
Which AI model is cheapest — ChatGPT, Claude, or Gemini? Gemini 3.1 Pro at $1.25 / $5 per million tokens. GPT-5.4 is $2.50 / $15. Claude Opus 4.6 is $15 / $75. For budget use, Gemini 2.5 Flash ($0.15 / $0.60) and Claude Haiku 4.5 ($0.80 / $4) are the best low-cost options.
What is the smartest AI model in 2026? GPT-5.4 scores 84 overall, Gemini 3.1 Pro scores 83, and Claude Opus 4.6 scores 81 on BenchLM. But "smartest" depends on the task — Claude leads math and HLE, Gemini leads agentic and multimodal, and GPT-5.4 leads coding and long-context reasoning.
Should I use ChatGPT, Claude, or Gemini for writing? Claude Opus 4.6 is widely preferred for long-form writing, editing, and prose. Its non-reasoning architecture produces more natural responses without chain-of-thought overhead. GPT-5.4 and Gemini 3.1 Pro are both capable but typically preferred for technical work.
All benchmark data is from our leaderboard. Compare models head-to-head on our comparison pages.
Get weekly benchmark updates in your inbox.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.
Share This Report
Copy the link, post it, or save a PDF version.
On this page
New model releases, benchmark scores, and leaderboard changes. Every Friday.
Free. Your signup is stored with a derived country code for compliance routing.
Claude Opus 4.6 vs GPT-5.4 head-to-head: benchmark scores, pricing, and when to use each. GPT-5.4 still leads overall at lower cost, but Claude remains strong on HLE, coding, multilingual, and long-form work.
Which Chinese LLM is best in 2026? We rank GLM-5, Kimi K2.5, DeepSeek V3.2, Qwen3.5, MiMo, Step 3.5, and more by benchmarks — coding, math, reasoning, and agentic tasks.
State of LLM benchmarks in 2026: top AI model rankings, category leaders, benchmark trends, open vs closed performance, pricing context, and methodology from BenchLM.