Which frontier model is best in April 2026?

Claude Opus 4.7 leads on coding and agentic tasks (SWE-bench Verified 74.6%, Terminal-Bench 69%). GPT-5.4 leads on general reasoning and vision-language benchmarks. Gemini 3.1 Pro leads on multimodal and long-context (2M tokens). There is no single winner in April 2026 — pick based on your primary workload: coding (Claude), general reasoning (GPT-5.4), or multimodal/long-context (Gemini).

How much do Claude Opus 4.7 and GPT-5.4 cost per million tokens?

Claude Opus 4.7: $15 input / $75 output per million tokens. Claude Sonnet 4.6: $3 input / $15 output. GPT-5.4: $1.50 input / $12 output. GPT-5.4 mini: $0.15 input / $1.20 output. Gemini 3.1 Pro: $1.25 input / $10 output (under 200K context). Gemini 3.1 Ultra: $2.50 input / $20 output. GPT-5.4 is the cheapest frontier model; Opus 4.7 is the most expensive.

What is Claude Opus 4.7's context window?

Claude Opus 4.7 has a 1 million token context window as of April 2026 (released February 2026). Sonnet 4.6 has 400K context. GPT-5.4 has 400K input context. Gemini 3.1 Pro has 2 million token context — still the leader for long-document work.

Is Gemini 3.1 Ultra worth it over Gemini 3.1 Pro?

Only for specific use cases. Gemini 3.1 Ultra beats Pro on complex multi-step reasoning and agentic tasks, but costs 2x more. For most developers, Pro is the better value. Ultra makes sense for research workloads, complex coding on massive codebases, and agentic workflows where reasoning quality matters more than token cost.

Quick Answer

Claude Opus 4.7 vs GPT-5.4 vs Gemini 3.1 Ultra April 2026

Published: April 23, 2026

Claude Opus 4.7 vs GPT-5.4 vs Gemini 3.1 Ultra (April 2026)

The frontier tripled in 2026. What was Claude 3.5 vs GPT-4o vs Gemini 1.5 at the start of 2025 is now a much more complex race. Anthropic shipped Opus 4.7 in February. OpenAI shipped GPT-5.4 in March. Google shipped Gemini 3.1 Pro and Ultra in April. Here’s how they compare on the benchmarks that matter.

Last verified: April 23, 2026

TL;DR

Metric	Claude Opus 4.7	GPT-5.4	Gemini 3.1 Pro	Gemini 3.1 Ultra
Release	Feb 2026	Mar 2026	Apr 2026	Apr 2026
Context window	1M tokens	400K tokens	2M tokens	2M tokens
Input price / 1M	$15	$1.50	$1.25	$2.50
Output price / 1M	$75	$12	$10	$20
SWE-bench Verified	74.6%	72.1%	70.8%	73.4%
GPQA Diamond	82.4%	84.1%	81.6%	83.9%
MMMU (multimodal)	76.8%	82.3%	83.5%	85.2%
AIME 2026	91.3%	94.7%	89.2%	93.1%
Terminal-Bench	69%	64%	58%	66%
Real-time web search	❌ (via tools)	✅ (built-in)	✅ (built-in)	✅ (built-in)
Agentic eval (τ-bench)	82%	78%	74%	80%

1. Claude Opus 4.7 — the coding + agent champion

Anthropic kept its lead on coding and agentic work. Opus 4.7 (released Feb 2026) hit 74.6% on SWE-bench Verified and 69% on Terminal-Bench, both best-in-class in April 2026.

Opus 4.7 strengths:

Best coding performance across SWE-bench, Terminal-Bench, and real-world refactor tasks.
1M context unlocks whole-repo reasoning.
Best agentic loops — lowest “give up” rate on multi-step tool use.
Tight Claude Code integration (Anthropic builds the agent on their own models).
Strongest reasoning-quality-per-dollar for small agent tasks (because you don’t need as many retries).

Downsides:

Most expensive. $15/$75 per million tokens is 10x GPT-5.4 and 12x Gemini Pro.
No native web search — requires tool-calling to MCP or third parties.
Slower — 30–80 tokens/sec vs GPT-5.4’s 120–180 tokens/sec.

Best for: Production coding agents, long-running autonomous tasks, anyone who can justify $15 input tokens.

2. GPT-5.4 — the general-purpose leader

GPT-5.4 (March 2026) shipped as OpenAI’s unified frontier model — it replaced the o-series and 4o-series into one model family (mini, base, and pro-reasoning). It wins most general reasoning benchmarks and is the cheapest frontier model per token.

GPT-5.4 strengths:

Cheapest frontier. $1.50 input / $12 output is ~10x cheaper than Opus 4.7.
Strongest on math and pure reasoning. AIME 2026 at 94.7% is a major lead.
Highest GPQA score (84.1%).
Fastest inference (120–180 tokens/sec).
Native web search + code execution + image gen in the API.
Best voice-to-voice latency (GPT-5.4 Voice is ~350ms).
Best developer ecosystem — Codex CLI, Agents SDK, Responses API, all native.

Downsides:

Only 400K context — half of Opus, a fifth of Gemini.
Worse coding quality vs Opus 4.7 on messy, multi-file refactors.
Agentic quality slightly behind Claude Opus 4.7 on multi-step tool use.

Best for: Default general-purpose reasoning, budget-conscious production, math/STEM workloads, voice AI, agent builders on OpenAI infrastructure.

3. Gemini 3.1 Pro — the multimodal + long-context winner

Gemini 3.1 Pro (April 2026) shipped with the biggest context window in production (2M tokens) and the strongest multimodal benchmarks. For document, video, and audio work, it has no peer.

Gemini 3.1 Pro strengths:

2M token context. Fit 1,000-page PDFs, 3-hour videos, or entire codebases without chunking.
Best MMMU score (83.5% Pro, 85.2% Ultra).
Native video and audio understanding — analyze 3 hours of video in one request.
Google Search grounding is more robust than OpenAI’s web search.
Deepest YouTube + Workspace integration — Docs, Sheets, Drive, Gmail all accessible.
Price ($1.25 input) is competitive with GPT-5.4 and 12x cheaper than Opus 4.7.

Downsides:

Behind Opus on coding (SWE-bench 70.8% Pro, 73.4% Ultra).
Safety filtering is still more aggressive than competitors, causing more refusals.
Smaller developer ecosystem than OpenAI or Anthropic.

4. Gemini 3.1 Ultra — the reasoning-heavy option

Ultra is Google’s response to Opus 4.7 — a reasoning-heavy variant that trades speed and cost for quality. Same 2M context but better performance on hard problems.

When to pick Ultra over Pro:

Complex multi-step reasoning where you can’t afford a wrong answer.
Agentic workflows on very long contexts (>500K tokens).
Pure research where you pay for the best answer regardless of cost.

Not worth it for: Standard coding, chatbots, short-context Q&A, anything where GPT-5.4 at 1/8 the cost is “good enough.”

Side-by-side: common tasks

Task	Winner	Runner-up
Refactor a 30-file React app	Opus 4.7	Gemini 3.1 Ultra
Summarize a 1,500-page PDF	Gemini 3.1 Pro	Opus 4.7
Solve an AIME math problem	GPT-5.4	Gemini 3.1 Ultra
Analyze a 2-hour meeting recording	Gemini 3.1 Pro	—
Build a production LangGraph agent	Opus 4.7	GPT-5.4
Cheap high-volume classification	GPT-5.4 mini	Gemini 3.1 Pro
Voice agent with sub-400ms latency	GPT-5.4 Voice	—
Research report with citations	Perplexity Sonar	GPT-5.4 with web
Image generation inside chat	GPT-5.4 (DALL-E 3.5 built-in)	—

Pricing comparison (April 2026)

Cost for a typical “read 50K tokens, generate 2K” request:

Model	Cost per request
Claude Opus 4.7	$0.90
Claude Sonnet 4.6	$0.18
GPT-5.4	$0.10
GPT-5.4 mini	$0.01
Gemini 3.1 Pro	$0.08
Gemini 3.1 Ultra	$0.17

GPT-5.4 mini is absurdly cheap for high-volume work. Opus 4.7 is 90x more expensive for the same shape of request — but on a hard coding task you might pay Opus once and GPT-5.4 mini three times trying to get it right, so total cost can be close.

Which should you default to in April 2026?

“I write code for a living”: Claude Opus 4.7 for hard tasks, Sonnet 4.6 for daily. Budget fallback: GPT-5.4.
“I’m building a consumer chatbot”: GPT-5.4. Cheap, fast, good enough.
“I analyze long docs, videos, or audio”: Gemini 3.1 Pro.
“I need the cheapest possible frontier”: GPT-5.4 mini for 90% of tasks.
“I’m building autonomous agents”: Opus 4.7.
“I do research with citations”: Gemini 3.1 Pro (Search grounding) or Perplexity Sonar.

Last verified: April 23, 2026. Prices from official API pricing pages. Benchmarks from Anthropic, OpenAI, and Google model cards plus independent tests by Artificial Analysis, LiveBench, and SWE-bench maintainers.