Here’s a concise, “all‑axes” comparison of the current top‑tier stacks: Gemini (2.5 Pro / 3 Pro), GPT (GPT‑4.1 / ChatGPT‑5 family), and Claude (Claude 4 Sonnet/Opus). I’ll focus on what actually differs in practice.openai+4
High‑level positioning
Gemini: Multimodal/context monster with tight Google integration and massive context; strongest when you mix text, code, images, audio, video or huge corpora.itecsonline+2
GPT: Most generalist and tool‑rich; very strong reasoning + coding with the broadest native multimodal stack and ecosystem (plugins, agents, third‑party tools).sigmabrowser+3
Claude: Deliberate thinker optimized for coding, long‑form analysis, safety, and “extended thinking”; strongest on complex software and careful explanations.anthropic+3
Capability table (late‑2025 / early‑2026 snapshot)
| Dimension | Gemini top tier (2.5 Pro / 3 Pro) | GPT top tier (GPT‑4.1 / ChatGPT‑5) | Claude top tier (Claude 4 Sonnet / Opus 4.x) |
|---|---|---|---|
| Core strength | Multimodal + huge context + Google integration.datastudios+2 | Balanced reasoning, coding, multimodal, tools.openai+2 | Best‑in‑class coding and careful reasoning.anthropic+3 |
| Reasoning (general) | Competitive, especially with long or multimodal inputs; slightly behind GPT/Claude on some pure text reasoning benchmarks.itecsonline+1 | Very strong general reasoning; 1M‑context “needle in haystack” and graphwalks evals show robust long‑context logic.openai+1 | Strongest on many structured reasoning / analysis tasks with “extended thinking” turned on.anthropic+2 |
| Coding | Good–very good; below Claude and often a bit under GPT on SWE‑bench‑style tests.itecsonline+2 | Strong, versatile coding and debugging across languages; not the top on SWE‑bench but solid.glbgpt+2 | Industry‑leading SWE‑bench Verified (≈72–75%, up to ≈80% with parallel compute).anthropic+4 |
| Multimodal I/O | Native text, images, audio, video in one stack; strong at video and document‑style vision.blog+3 | Full unified multimodal (text, image, audio, video) with mature tools; very flexible.openai+2 | Primarily text‑centric with maturing image/PDF input; less emphasis on full video/audio pipeline.anthropic+3 |
| Context window | Up to ≈2M tokens on Pro in Vertex / high tiers; Flash also very large.docs.cloud.google+4 | Up to 1M tokens in GPT‑4.1 family (API), smaller in standard UI.learn.microsoft+4 | Commonly ≈200k in Sonnet/Opus 4; up to 500k in some enterprise tiers.platform.claude+2 |
| Long‑context quality | Designed for massive document/code/video workloads; strong but not always best at fine‑grain reasoning inside huge contexts.datastudios+2 | Very good: 1M‑token “needle” and graphwalk benchmarks show robust retrieval in long context.openai+1 | Good, but smaller max windows; shines more in careful reasoning than sheer size.platform.claude+1 |
| Speed / latency | Flash models extremely fast (hundreds of tokens/s, sub‑0.3s TTFT); Pro slower but still competitive.deeplearning+2 | Balanced; faster than earlier GPT‑4, not as fast as Gemini Flash in most reports.glbgpt+2 | Sonnet often mid‑pack for speed; extended‑thinking modes intentionally slower for harder tasks.anthropic+1 |
| Pricing (API ballpark) | Aggressive on context (lots of tokens per dollar); very good value for multimodal + long context.google+2 | Generally mid‑range per million tokens; good value given ecosystem and tools.openai+1 | Tends to be pricier at the top tiers, but cost justified for orgs that value coding + safety.anthropic+2 |
| Safety / alignment | Strong Google safety stack, guardrails, and filters; conservative on some topics.blog+2 | Mainstream OpenAI approach; improved guardrails, but more permissive than Claude on many tasks.openai+2 | Most safety‑constrained; Anthropic centers “constitutional AI” and conservative defaults.anthropic+2 |
| Tooling & agents | Deep integration with Google (Workspace, Search, Maps, YouTube) plus Vertex AI; agentic features and Deep Research in Gemini Advanced.blog+3 | Rich tool ecosystem: function calling, workflows, agents, plugins; strong third‑party ecosystem.openai+2 | Strong for enterprise agents (Bedrock, Vertex, Anthropic API), with emphasis on reliability and governance.anthropic+2 |
| Ecosystem & adoption | Natural choice for Google‑centric orgs; strong in data/Docs/Sheets, Android, and Chrome contexts.gemini+2 | Broadest developer and consumer footprint; many libraries, UIs, and SaaS products built around GPT APIs.openai+2 | Popular in enterprises that care about risk, compliance, and code quality; embedded in tools like GitHub Copilot agents and Bedrock.anthropic+2 |
Detailed axes
1. Reasoning and long‑context work
Gemini: Very strong at multi‑step reasoning when the task uses its strengths—huge context or multimodal inputs—but independent testing often puts it just below Claude for hard coding/logic and roughly on par or slightly under GPT‑4.1 on pure text benchmarks.datastudios+4
GPT: Excellent generalist; 1M‑token context plus strong “needle‑in‑a‑haystack” and graphwalk scores show it can both hold and use massive context effectively.datacamp+1
Claude: Often top on structured reasoning and careful analysis, especially when extended‑thinking is enabled, at the cost of latency and price.anthropic+3
If you’re doing long technical reports or philosophical analysis, Claude usually gives the most coherent, reflective write‑ups; GPT is close and more versatile; Gemini is best when those reports must integrate many files, images, or long transcripts.
2. Coding and software engineering
Benchmarks: Multiple reports put Claude 4 Sonnet/Opus at the top of SWE‑bench‑style benchmarks (≈72–75%+, up to ≈80% with parallel compute), with Gemini 2.5 Pro lagging and GPT‑4.1 in the middle.apidog+4
Developer workflow:
Gemini: Great when your repos live in Google Cloud, and when you need to reason over diagrams, logs, or UI screenshots as part of coding.docs.cloud.google+3
GPT: Best “all‑rounder” for IDE integrations, agents, and quick prototypes; wide tooling support (Cursor, VS Code assistants, etc.).glbgpt+3
Claude: Favored for refactoring large codebases and debugging subtle issues; popular for “trust it with a big monorepo” tasks.entelligence+4
For your kind of deep, systems‑level coding or analysis, Claude is generally the best first pick; GPT is the second choice for breadth and tools; Gemini is ideal when the code problem is entwined with data, docs, or visual context.
3. Multimodal (text, image, audio, video)
Gemini: Strong emphasis on multimodality—image, audio, and video understanding plus generation through related models (e.g., Veo, Imagen) in the Google AI Pro/Ultra bundles.blog+4
GPT: Highly capable unified multimodal model embedded in ChatGPT‑5/4.1, handling images, audio, and video in a single conversational flow, with many creative tools wrapped around it.openai+3
Claude: Primarily text‑first; image/PDF inputs are supported in many deployments, but it does not yet lean as hard into full video/audio workflows as Gemini/GPT.allmates+3
For drone footage, environmental imagery, and long video or audio logs, Gemini or GPT currently give you more leverage than Claude.
4. Context windows, memory, and “agentic” behaviour
Context: Gemini often leads on raw context size (up to ≈2M tokens), GPT offers up to 1M, Claude up to 200–500k depending on tier.datastudios+5
Use of context: GPT shows particularly strong ability to actually retrieve specific content from giant contexts; Claude sacrifices raw size but tends to reason deeply over what it has; Gemini sits between, with emphasis on multimodal long‑context workloads.datacamp+3
Agents & tools: All three support tool calling and multi‑step workflows; GPT has the most mature ecosystem, Gemini is tightly coupled to Google services, Claude leans into enterprise agents with safety and governance knobs.cloud.google+5
For your “big corpus” hydrology/indigenous‑knowledge research, Gemini and GPT are attractive for sheer context; Claude is ideal when you want slower but more interpretable chains of reasoning over smaller curated chunks.
5. Safety, reliability, and “feel”
Gemini: Conservative content filters and Google’s safety stack; good for organizations worried about brand risk but sometimes frustrating for edgy or controversial topics.blog+2
GPT: Middle of the road; stronger safety than early GPT‑4 but not as locked‑down as Claude on some sensitive themes.glbgpt+2
Claude: Most risk‑averse, with “constitutional AI” and strong refusal behavior; often preferred for regulated sectors and sensitive domains.remio+2
Subjectively: Claude often “feels” like a careful human expert; GPT like a flexible all‑purpose collaborator; Gemini like a powerful multimodal lab instrument wired into Google.
If you tell me your main dimensions (e.g., coding vs. research vs. multimedia vs. philosophy) and whether cost/latency matter, I can give a more pointed recommendation like “for X, default to Claude; for Y, switch to Gemini; use GPT when you need Z.”
