DeepSeek V4 vs Claude Opus 4.7 vs GPT-5.5 (April 2026)
DeepSeek V4 vs Claude Opus 4.7 vs GPT-5.5 (April 2026)
DeepSeek shipped V4 yesterday. The 1.6 trillion parameter open-weight model lands within striking distance of Claude Opus 4.7 and GPT-5.5 — at roughly one-sixth the API cost. Here’s how the three flagships actually compare as of April 25, 2026.
Last verified: April 25, 2026
TL;DR
| DeepSeek V4-Pro | Claude Opus 4.7 | GPT-5.5 | |
|---|---|---|---|
| SWE-bench Verified | 80.6% | 80.8% | 76.4% |
| Terminal-Bench 2.0 | 67.9% | 65.4% | 82.7% |
| LiveCodeBench | 93.5% | 88.8% | 91.2% |
| Context window | 1M tokens | 1M tokens | 400K tokens |
| Input price (per 1M) | $1.74 | $5.00 | $5.00 |
| Output price (per 1M) | $3.48 | $25.00 | $30.00 |
| Open weights | ✅ Yes | ❌ No | ❌ No |
| Best for | Volume + cost | Deep coding quality | Long autonomous runs |
DeepSeek V4-Pro — the cost killer
What launched: Two preview variants on April 24, 2026 — V4-Pro (1.6T parameters, 49B active) and V4-Flash (lighter, faster). 1M token context. MoE architecture trained partly on Huawei Ascend 950 chips. Open weights on Hugging Face.
Benchmarks (DeepSeek-reported, third-party verification ongoing):
- SWE-bench Verified: 80.6%
- Terminal-Bench: 67.9%
- LiveCodeBench: 93.5%
- Agentic Coding (SOTA among open models)
- World knowledge: leads all open models, trails only Gemini 3.1 Pro
Strengths:
- Cheapest near-frontier model by a wide margin
- 1M token context (full monorepo, full books, full codebases)
- Open weights — you can self-host or fine-tune
- Strong multilingual + Chinese/English bilingual
- Runs on Huawei Ascend 950 supernodes (China-friendly deployment)
Weaknesses:
- No native computer use yet (vs GPT-5.5)
- Shorter autonomous task horizon than GPT-5.5
- Smaller MCP/tool ecosystem than Anthropic
- API latency ~110 tokens/sec (slower than GPT-5.5’s 140)
- Custom license (not OSI open source)
Claude Opus 4.7 — still the deep-coding king
What it is: Anthropic’s flagship since March 2026. 1M context, 200K reasoning budget, mature MCP tool ecosystem.
Strengths:
- Highest SWE-bench Verified score by 0.2 points (80.8%)
- Best multi-file refactoring quality
- Deepest MCP tool ecosystem (hundreds of community + first-party tools)
- JetBrains support
- Best instruction following and safety
Weaknesses:
- 5–7× more expensive than DeepSeek V4 on output
- Loses Terminal-Bench 2.0 to GPT-5.5 by a wide margin (65.4% vs 82.7%)
- Closed weights — no self-hosting
- ~55 tokens/sec output speed
Best for: Production codebases where review cost > token cost, JetBrains shops, refactor-heavy work, anyone with an established MCP tool stack.
GPT-5.5 — the autonomous-agent leader
What it is: OpenAI’s flagship since April 23, 2026. Native computer use, Dynamic Reasoning Time (7+ hour single-task runs), 400K context, default in Codex and Agents SDK.
Strengths:
- Best Terminal-Bench 2.0 score (82.7%)
- Best τ²-Bench and GDPval scores
- Native computer use without plugins
- 7+ hour autonomous task horizon
- Tightest IDE integration (Codex IDE, Codex Cloud)
- 140 tokens/sec output
Weaknesses:
- Most expensive output ($30/M)
- Smaller context window (400K vs 1M)
- Locked to OpenAI surfaces (or via API)
- Lower SWE-bench than Opus 4.7 and V4-Pro
Best for: Autonomous coding agents, computer-use workflows, anything that runs unattended for hours, ChatGPT-native users.
Pricing math: a real example
For a 100-million-token monthly load (50M input + 50M output):
| Model | Monthly cost |
|---|---|
| DeepSeek V4-Pro | $261 |
| Claude Opus 4.7 | $1,500 |
| GPT-5.5 | $1,750 |
DeepSeek V4-Pro is ~6× cheaper than Claude Opus 4.7 and ~7× cheaper than GPT-5.5 at this volume. For a startup processing millions of agent calls, this is the difference between $3K/month and $20K/month.
When to pick which
Pick DeepSeek V4-Pro when:
- You’re running high-volume LLM workloads (RAG, batch generation, internal tools)
- 80-95% of frontier quality is enough
- You need 1M context
- You want the option to self-host
- You’re building for the China market (Huawei Ascend support)
Pick Claude Opus 4.7 when:
- Code quality on production PRs matters more than token cost
- You’re in a JetBrains shop
- You’ve invested in the MCP tool ecosystem
- You need Anthropic’s safety + instruction-following profile
Pick GPT-5.5 when:
- You need 7+ hour autonomous runs
- Computer use is core to the workflow
- You’re ChatGPT-native or already on Codex
- Terminal-Bench 2.0 scores matter (DevOps automation, sysadmin agents)
The smart play: route by task
Most serious teams in April 2026 are no longer picking one model — they’re routing:
- Cheap bulk work → DeepSeek V4-Flash ($0.14 / $0.28)
- Standard coding tasks → DeepSeek V4-Pro
- Critical PR review + refactor → Claude Opus 4.7
- Long autonomous + computer use → GPT-5.5
Tools like LangGraph, LiteLLM, OpenRouter, and Helicone make multi-model routing trivial. The question is no longer “which model?” but “which router strategy?”
What this means for the market
DeepSeek V4 is the second time DeepSeek has compressed prices in 18 months. The first time (R1, January 2025) wiped $600B off Nvidia in a day. This time, the response is more measured — but Anthropic and OpenAI now face real pricing pressure on the 80-95% quality tier.
Expect:
- Sonnet 4.7 / 4.8 priced more aggressively in Q2
- More OpenAI tiered pricing (GPT-5.5-mini, GPT-5.5-nano)
- Deeper integration of open-weight models into commercial agent stacks
For builders, this is the best moment in AI coding history: near-frontier quality at single-digit dollar costs per million tokens.
Last verified: April 25, 2026. Sources: DeepSeek V4 release notes (api-docs.deepseek.com), VentureBeat, TechCrunch, Reuters, Hugging Face deepseek-ai/DeepSeek-V4-Pro, Anthropic pricing, OpenAI pricing.