Quick navigation: TL;DR · SWE-bench · Pricing · Long context · Tool use · Side-by-side · Pick by use case · FAQ · Sources
In May 2026 there are two model families that 80% of professional engineering teams reach for: Claude (Anthropic) and GPT-5.x (OpenAI). After a quiet January and February, both vendors shipped major updates within a week of each other in April: Claude Opus 4.7 on April 16, and GPT-5.5 on April 23.
This is the head-to-head for coding work specifically, with verified figures from the SWE-bench Verified leaderboard and vendor pricing pages.
TL;DR {#tldr}
- GPT-5.5 leads SWE-bench Verified at 88.7%, narrowly ahead of Claude Opus 4.7 (Adaptive) at 87.6%. The gap is real but small.
- Claude is cheaper for output-heavy work: Opus 4.7 at $5/$25 per M vs GPT-5.5 at $5/$30 per M. For high-output agent loops, Claude wins on cost.
- Sonnet 4.6 is the value pick: $3/$15 with 1M-token context. Most teams use Sonnet daily and reach for Opus only on hard problems.
- GPT-5 mini and nano are dramatically cheaper for bulk inference: $0.25/$2 and $0.05/$0.40 per M tokens.
For most professional engineering work in 2026: Sonnet 4.6 daily, Opus 4.7 for hard problems, GPT-5.5 for the highest-difficulty SWE-bench-style tasks.
SWE-bench Verified (May 2026 leaderboard) {#swebench}
| Rank | Model | Score |
|---|---|---|
| 1 | GPT-5.5 (OpenAI, April 23, 2026) | 88.7% |
| 2 | Claude Opus 4.7 (Adaptive) (Anthropic, April 16, 2026) | 87.6% |
| – | GPT-5.3 Codex | 85.0% |
| – | Claude Opus 4.5 | 80.9% |
| – | Claude Opus 4.6 | 80.8% |
| – | DeepSeek V4-Pro (open-weight 1.6T MoE) | 80.6% |
| – | Gemini 3.1 Pro | 80.6% |
Reading the gap: 1.1 percentage points on a benchmark with measurement noise is small. In day-to-day coding the differences show up more in workflow fit than raw capability.
Pricing (verified May 2026) {#pricing}
Anthropic Claude API:
| Model | Input ($/M) | Output ($/M) | Context |
|---|---|---|---|
| Haiku 4.5 | $1.00 | $5.00 | 200K |
| Sonnet 4.6 | $3.00 | $15.00 | 1M |
| Opus 4.7 | $5.00 | $25.00 | 200K (1M tier separate) |
- Prompt caching: 90% discount on cached input
- Batch processing: 50% off all tokens
- Note: Opus 4.7 ships with a new tokenizer that can produce up to 35% more tokens for the same input compared to Opus 4.6 — effective cost-per-request can be higher
OpenAI GPT-5.x API:
| Model | Input ($/M) | Output ($/M) |
|---|---|---|
| GPT-5.5 | $5.00 | $30.00 |
| GPT-5.5-pro | $30.00 | $180.00 |
| GPT-5.1 Standard | $1.25 | $10.00 |
| GPT-5 Mini | $0.25 | $2.00 |
| GPT-5-nano | $0.05 | $0.40 |
- GPT-5.5 above 272K input tokens: 2× input / 1.5× output for the full session
- Regional/data-residency endpoints: 10% uplift on GPT-5.5
- Prompt caching: 90% discount on cached input
Cost reading: For typical agent loops with prompt caching:
- Sonnet 4.6 at $3 input is meaningfully cheaper than GPT-5.5 at $5 input
- Opus 4.7 vs GPT-5.5: $5 input each, but Opus output is $25 vs GPT-5.5 output $30 — Claude wins on output-heavy work
- For bulk inference: GPT-5-nano at $0.05/$0.40 is the cheapest credible coding model in either lineup
Long context {#context}
Claude Sonnet 4.6: 1M-token context at standard pricing. Opus 4.7: 200K standard, 1M-tier available separately. Haiku 4.5: 200K.
GPT-5.5: 272K standard before pricing changes; full max higher with the >272K-token surcharge.
For monorepo-scale work, Sonnet 4.6 at 1M tokens is the strongest default in the lineup — same context as the 200K tiers, four to five times the headroom.
Tool use & agent workflows {#tools}
Both vendors ship excellent function-calling. The execution differences:
Claude:
- More reliable JSON tool-call output; rare malformed calls in practice
- Native integration with Claude Code — Anthropic's CLI agent
- MCP (Model Context Protocol) is Anthropic-led, an open standard with a reference implementation at modelcontextprotocol.io; broadest tool ecosystem in 2026
OpenAI GPT-5.x:
- Excellent function-calling for narrow APIs
- ChatGPT advanced data analysis remains best-in-class for one-off Python work
- No first-party CLI agent equivalent to Claude Code in 2026 (third-parties fill the gap)
For build-your-own-agent work in 2026, MCP plus tool-call reliability still tilt most teams toward Claude.
IDE & CLI ecosystem {#ecosystem}
This is where the choice often happens for engineers in practice.
Claude appears in:
- Claude Code (Anthropic's CLI agent — strongest agentic tool in 2025-2026)
- Cursor (selectable; Cursor lists Sonnet 4.5 and Opus 4.6 alongside its own Composer model)
- GitHub Copilot Pro+ added Claude Opus 4.6 access in March 2026 ($39/mo tier)
- Cline, Aider, Continue (BYO model)
- Web claude.ai with Projects and Artifacts
GPT-5.x appears in:
- GitHub Copilot (Microsoft / GitHub default for many tiers)
- Cursor (selectable; "GPT-5.3" listed in their model lineup)
- ChatGPT desktop app with Code Interpreter
- Most legacy AI plugins (longest tail of integrations)
For full IDE landscape: AI Coding Assistants 2026.
Side-by-side {#table}
| Aspect | Claude (Sonnet 4.6 / Opus 4.7) | GPT-5.5 |
|---|---|---|
| SWE-bench Verified | Opus 4.7: 87.6% | 88.7% (#1) |
| Latest release | Opus 4.7: April 16, 2026 | April 23, 2026 |
| Cheapest tier | Haiku 4.5 ($1/$5) | GPT-5-nano ($0.05/$0.40) |
| Mid tier | Sonnet 4.6 ($3/$15) | GPT-5.1 ($1.25/$10) |
| Top tier (input/output $/M) | Opus 4.7 ($5/$25) | GPT-5.5 ($5/$30) |
| Long context (standard) | Sonnet 4.6: 1M | GPT-5.5: 272K (then 2×/1.5×) |
| First-party CLI agent | Claude Code | None |
| Tool calling standard | MCP (open) | Native function-calling |
| Prompt caching | 90% discount | 90% discount |
| Batch discount | 50% | (per docs) |
Pick by use case {#pick}
Building agents or multi-step tools → Claude. MCP, tool-call reliability, and Claude Code give it the edge.
Tab completion / inline suggestions → either, depending on your IDE pick. Cursor lets you switch; Copilot defaults to GPT-5.x with Claude Opus 4.6 on Pro+.
Long-context / monorepo work → Sonnet 4.6 (1M). The context advantage compounds and the price ($3/$15) is competitive.
Bulk inference, cheapest credible model → GPT-5-nano ($0.05/$0.40). Half the cost of Haiku 4.5 input, eighth the output cost.
Hardest SWE-bench-style problems → GPT-5.5 (88.7%). For the marginal 1.1 points over Opus 4.7, you pay roughly the same input rate and 20% more on output.
Output-heavy agent loops → Opus 4.7 ($5/$25 vs GPT-5.5's $5/$30 output). The output gap matters when the loop produces lots of code.
Code review and PR analysis → Claude. More disciplined plan-before-act behavior in practice.
Python data science / Jupyter → GPT-5.x via ChatGPT Code Interpreter. Still the best loop for one-off analysis work.
For prompt patterns that work well with both: Prompt Engineering 2026.
FAQ {#faq}
Should I use Claude or GPT-5.5 in Cursor?
Cursor lets you switch and lists Claude Sonnet 4.5, Claude Opus 4.6, GPT-5.3, Gemini 3 Pro, and its own Composer model (released October 2025, optimized for Cursor's agent loop, ~4× faster than similarly-capable models). The 2026 default for many users: Composer for fast inline edits, Claude or GPT-5.5 for harder tasks via Composer/Agent mode.
Is Claude Opus 4.7 worth 5× the cost of Sonnet?
For routine coding: no. For multi-step reasoning, complex refactors, code review of large PRs: often yes. The Sonnet 4.6 → Opus 4.7 gap on SWE-bench is several points; the cost gap is 5×.
What about Gemini 3 / DeepSeek V4?
Gemini 3.1 Pro scores 80.6% on SWE-bench Verified — solid but not at the top. DeepSeek V4-Pro (released April 24, 2026, open-weight, 1.6T MoE / 49B active, MIT license) scores 80.6% as well — the best open-weight option, though it requires datacenter hardware to self-host.
Can I run Claude or GPT-5.5 locally?
No. Both are closed-weights. For local options that are competitive (not equal): Best Local LLMs for Consumer Hardware (2026).
Which has fewer hallucinations on library names?
Anecdotally Claude in 2026 testing, but both still hallucinate. Always grep before trusting an API exists.
Is there really a "Claude Mythos" model at 93.9%?
The SWE-bench Verified leaderboard listed "Claude Mythos Preview" at 93.9% in early 2026 reporting. As a preview model it isn't the public default; treat it as a research signal, not a production option.
Bottom Line
The 2026 default stack:
- Daily driver: Claude Sonnet 4.6 ($3/$15, 1M context)
- Hard problems: Claude Opus 4.7 or GPT-5.5
- Bulk inference / cost-sensitive: GPT-5-nano or Claude Haiku 4.5
- Top SWE-bench score on a single attempt: GPT-5.5 (88.7%)
The differences narrowed in 2026. The choice is now driven by workflow fit — which IDE you live in, which CLI you trust, which standards you've built tooling around — not raw capability gaps.
Top comments (0)