The Best LLM for Reasoning in 2026 (Benchmarked)
Which LLM reasons best in 2026? We compare Claude Opus 4.8, GPT-5.5, and Gemini 3.1 Pro on GPQA Diamond, Humanity's Last Exam, and AA-LCR long-context retrieval.
Reasoning is the capability that separates models that can plan, infer, and solve novel problems from those that pattern-match well on familiar prompts. This post uses three rigorous evaluations to rank leading models in 2026.
The benchmarks that reveal reasoning ability
General knowledge tests like MMLU are largely saturated — top models score above 90% — which means they cannot distinguish between models at the frontier. These three evals still discriminate meaningfully:
- GPQA Diamond — 448 expert-written questions in biology, physics, and chemistry, validated by PhD holders. The "diamond" subset is the hardest tier, requiring genuine domain expertise rather than memorised facts. Read what GPQA measures for the full methodology.
- Humanity's Last Exam — a crowd-sourced set of the hardest questions humans could write, spanning mathematics, science, law, and the humanities. Models struggle; scores below 60% even with tools are typical.
- AA-LCR (Long Context Retrieval) — measures a model's ability to retrieve and reason over facts buried inside very long documents. This tests a different facet of reasoning: attention fidelity under pressure.
For guidance on how to interpret these scores, see the complete guide to LLM benchmarks.
GPQA Diamond: graduate-level science
GPQA Diamond is currently close to saturation at the top of the field, which makes small differences meaningful:
| Model | GPQA Diamond |
|---|---|
| Mythos Preview | 94.6% |
| Gemini 3.1 Pro | 94.3% |
| Claude Opus 4.7 | 94.2% |
| Claude Opus 4.8 | 93.6% |
| GPT-5.5 | 93.6% |
All five models cluster within a 1-point band. Gemini 3.1 Pro leads the production models at 94.3%, followed closely by Opus 4.7 at 94.2%. Opus 4.8 and GPT-5.5 are tied at 93.6%. Given these margins, GPQA Diamond should be considered saturated for discriminating between today's top models.
Humanity's Last Exam: the frontier test
HLE is the evaluation that still has room to grow — no model reaches 60% even with tool access. It is the best current signal for frontier reasoning.
| Model | HLE (no tools) | HLE (with tools) |
|---|---|---|
| Claude Opus 4.8 | 49.8% | 57.9% |
| Gemini 3.1 Pro | 44.4% | 51.4% |
| GPT-5.5 | 41.4% | 52.2% |
Opus 4.8 leads both conditions: 49.8% without tools and 57.9% with tools. Gemini 3.1 Pro (51.4% with tools) leads GPT-5.5 (52.2%) by a narrow margin in the tool-assisted condition, while GPT-5.5 trails Gemini without tools.
The tool-use gap is worth noting: Opus 4.8 gains 8.1 percentage points when given tool access, compared to 7.0 for GPT-5.5 and 7.0 for Gemini 3.1 Pro. Opus 4.8 is better at leveraging external resources when reasoning through hard problems.
AA-LCR: reasoning over long documents
AA-LCR tests a distinct reasoning mode: finding and connecting information spread across very long contexts. Only two models have published results here:
| Model | AA-LCR |
|---|---|
| GPT-5.5 | 74.3% |
| Claude Opus 4.7 | 70.3% |
| Claude Opus 4.8 | 67.7% |
| Gemini 3.1 Pro | n/a |
GPT-5.5 leads at 74.3%, ahead of Opus 4.7's 70.3% and Opus 4.8's 67.7%. Gemini 3.1 Pro has not reported results on this benchmark. For workloads that require processing and reasoning over large document collections — legal review, research synthesis, long-form code analysis — GPT-5.5's long-context architecture gives it a real edge.
How do reasoning and coding intersect?
Strong reasoning capability tends to improve agentic coding performance too — a model that can plan multi-step solutions and catch logical errors in its own output performs better on SWE-bench. But the correlation is not 1:1: Opus 4.8 leads SWE-bench Pro by a wide margin despite being in the middle of the reasoning pack on GPQA. The best LLM for coding guide has the full coding-benchmark breakdown.
You can explore all benchmark results in our live benchmark comparison table, or compare two specific models in Opus 4.8 vs GPT-5.5 and Opus 4.8 vs Gemini 3.1 Pro.
Key takeaways
- Best for frontier reasoning: Claude Opus 4.8 — leads Humanity's Last Exam in both conditions by 5-6 points.
- Best for graduate-level science (GPQA): The top models are essentially tied; Gemini 3.1 Pro has a 0.7-point edge but GPQA is near saturation.
- Best for long-context reasoning: GPT-5.5 leads AA-LCR (74.3%) — important for document-heavy workloads.
- Tool-augmented reasoning matters: every model gains significantly with tool access on HLE; build your stack to take advantage of this.
- Read the complete LLM benchmark guide to understand how these evals are designed and what pitfalls to avoid when reading the numbers.
