Multi-dimensional Model & Plan Comparison
Compare pricing, coding pass rates, context windows, and estimated monthly invoices side-by-side. Generate shareable posters with 1 click.
Popular Comparisons:
DeepSeekVerified
DeepSeek-V4 (Next-Gen MoE)
★ Save 89%
Input$0.55 / 1M
Output$1.65 / 1M
Context131K
CursorBench Pass Rate—
AnthropicVerified
Claude Opus 5.5
★ Massive Context 1M
Input$4.00 / 1M
Output$20.00 / 1M
Context1M
CursorBench Pass Rate57.8%
Pick your workflow, then your budget
Estimates use our price snapshot, excluding cache, retries, taxes and tools. Check availability for preview and legacy models.
Workload cost · USD (lower costs less)
DeepSeek-V4 (Next-Gen MoE)$8.80
Claude Opus 5.5$80.00
Context capacity · tokens (not recall accuracy)
DeepSeek-V4 (Next-Gen MoE)131,072
Claude Opus 5.51,000,000
CursorBench 4.0 · %
DeepSeek-V4 (Next-Gen MoE)No verified data
Claude Opus 5.557.8%
Tool reliability, long-context recall and same-harness SWE-bench: untested, not zero.
CursorBench · 2026-10-20 ↗Patch review example: why does an empty array slip through?
Editorial example, not measured model output. Review boundary contracts and regression tests; this is not a model ranking.
export function mean(values: number[]) {
return values.reduce((a, b) => a + b, 0)
/ values.length;
}
// mean([]) => NaN
// Missing an explicit empty-input contract⚙️ Select ModelDeepSeek-V4 (Next-Gen MoE) vs Claude Opus 5.5
Slot 1DeepSeek
Slot 2Anthropic
Slot 3
💰 Monthly Cost Simulation
Simulate monthly cost differences based on your estimated token usage volume
DeepSeek-V4 (Next-Gen MoE)
$8.80/ mo
(in: $5.50 + out: $3.30)
Claude Opus 5.5
$80.00/ mo
(in: $40.00 + out: $40.00)
| Attribute | DeepSeek-V4 (Next-Gen MoE)DeepSeek | Claude Opus 5.5Anthropic |
|---|---|---|
| Input | $0.55 | $4.00 |
| Output | $1.65 | $20.00 |
| Context | 131K | 1M |
| CursorBench Pass Rate | — | 57.8% |
| Status | Verified | Verified |
| Tags & Capabilities | Open weights, MoE, Ultra low cost, SWE-bench 68.9%, DeepSeek | New, Flagship, Reasoning, Coding, Agentic, Adaptive thinking, SOTA |
| LMArena Code | #— | #1 |
| LMArena Agent | #— | #1 |
| CursorBench | #— | #1 |
| Artificial Analysis | #— | #1 |
| Vals AI | #— | #2 |
| LiveBench | #— | #2 |
| LMArena Text | #— | #2 |