Model comparison
Claude Opus 5 vs DeepSeek V4-Flash
Anthropic against DeepSeek, compared on context, price, and verified benchmark results.
Catalog record checked August 14, 2026; individual provider fields may change.
Anthropic
Claude Opus 5
Frontier
DeepSeek
DeepSeek V4-Flash
Budget · Open weights
| Specification | Claude Opus 5 | DeepSeek V4-Flash |
|---|---|---|
| Provider | Anthropic | DeepSeek |
| Tier | Frontier | Budget |
| Context window | 1M | 1M |
| Max output | 128K | Winner: 384K |
| Input / 1M tokens | $5 | Winner: $0.14 |
| Output / 1M tokens | $25 | Winner: $0.28 |
| Weights | Closed | Open |
| Parameters | Not disclosed | 284B total / 13B active (MoE) |
| Reasoning levels | low, medium, high, xhigh, max | low, high, max |
| Modalities | text, image | text |
| Released | July 24, 2026 | July 31, 2026 |
| Artificial Analysis Intelligence Index [max] (2026-08-14) | Winner: 63 | 52 |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Pricing tiers: DeepSeek V4-Flash: Current list is $0.14/$0.28 per million tokens (cache miss / output) until 2026-08-16 16:00 UTC. From then, official peak/off-peak rates: off-peak $0.22/$0.66, peak $0.44/$1.32 (cache miss / output). Peak hours are 01:00–04:00 and 06:00–10:00 UTC.
Claude Opus 5
Anthropic's frontier tier, and ahead of Fable 5 on both recorded benchmarks at half the price.
Best for
- Agentic coding
- Long-context analysis
- Multi-step engineering work
Watch out
Output tokens cost five times input — long generations dominate the bill.
DeepSeek V4-Flash
Open-weight price-performance pick: MIT weights, 1M context, and API rates far below closed budget tiers.
Best for
- Cost-sensitive hosted agents
- High-volume coding assist
- Open-weight deployments with cluster VRAM
Watch out
API list prices move to peak/off-peak from 2026-08-16 16:00 UTC (see pricing note). Self-hosting the ~284B MoE still needs roughly 90–170GB+ class VRAM depending on quant — not a laptop budget build. DeepSWE snapshot also uses the shared mini-swe-agent harness — verify cost, effort, and serving conditions before treating the result as a forecast.
Benchmark
DeepSWE 1.1 in context
Both models shown against the wider field, with cost per completed task alongside the score.
Local leader
Claude Opus 5 [max]
74%
Rows shown
24
Highest published reasoning effort per model (not best Pass@1)
Snapshot date
2026-08-13
Mirrored from deepswe.datacurve.ai
Better is toward the top-right (higher pass rate, lower cost). X-axis is reversed to match DeepSWE’s public chart. v1.1 uses average cost / tokens / steps; v1 uses published medians.
| # | Model | Pass@1 | Cost / task | Tokens / task | Steps / task |
|---|---|---|---|---|---|
| 1 | Claude Opus 5 [max] | 74% | $11.84 | 118k | 99 |
| 2 | GPT-5.6 Sol [max] | 73% | $8.39 | 60k | 61 |
| 3 | Claude Fable 5 [max] | 70% | $21.63 | 119k | 88 |
| 4 | GPT-5.6 Terra [max] | 70% | $4.95 | 72k | 76 |
| 5 | Kimi K3 [max] | 69% | $4.65 | 82k | 98 |
| 6 | GPT-5.6 Luna [max] | 67% | $3.03 | 73k | 102 |
| 7 | GPT-5.5 [xhigh] | 67% | $7.23 | 46k | 82 |
| 8 | Grok 4.6 [xhigh] | 67% | $5.50 | 71k | 87 |
| 9 | Gemini 3.7 Flash [high] | 65% | $2.18 | 107k | 125 |
| 10 | DeepSeek V4-Pro [max] | 63% | $0.24 | 106k | 155 |
| 11 | Claude Opus 4.8 [max] | 59% | $13.22 | 135k | 120 |
| 12 | Qwen3.8-Max [xhigh] | 58% | $3.73 | 95k | 111 |
| 13 | Muse Spark 1.2 [xhigh] | 55% | $3.70 | 99k | 101 |
| 14 | Claude Sonnet 5 [max] | 54% | $26.40 | 214k | 268 |
| 15 | Grok 4.5 [high] | 54% | $2.42 | 36k | 61 |
| 16 | DeepSeek V4-Flash [max] | 53% | $0.10 | 108k | 153 |
| 17 | Muse Spark 1.1 [xhigh] | 53% | $2.36 | 74k | 96 |
| 18 | GPT-5.4 [xhigh] | 52% | $5.65 | 71k | 70 |
| 19 | Gemini 3.6 Flash [high] | 47% | $4.42 | 96k | 117 |
| 20 | GLM 5.2 [max] | 44% | $3.92 | 78k | 129 |
| 21 | Gemini 3.5 Flash [high] | 36% | $3.45 | 76k | 105 |
| 22 | Kimi K2.7 Code | 31% | $2.82 | 59k | 149 |
| 23 | Claude Sonnet 4.6 [high] | 30% | $5.52 | 76k | 134 |
| 24 | Gemini 3.1 Pro [high] | 12% | $2.14 | 28k | 76 |
DeepSWE “Best” picks the highest published reasoning effort per model (not the highest pass rate). Small gaps may not be statistically meaningful — confirm on deepswe.datacurve.ai.
Common questions
Claude Opus 5 vs DeepSeek V4-Flash
Answered from the verified figures on this page rather than general guidance.
Is Claude Opus 5 or DeepSeek V4-Flash cheaper for input?
DeepSeek V4-Flash is cheaper at $0.14 per million input tokens, against $5 for Claude Opus 5 — roughly 36× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; DeepSeek V4-Flash has tiered pricing: Current list is $0.14/$0.28 per million tokens (cache miss / output) until 2026-08-16 16:00 UTC. From then, official peak/off-peak rates: off-peak $0.22/$0.66, peak $0.44/$1.32 (cache miss / output). Peak hours are 01:00–04:00 and 06:00–10:00 UTC.
Is Claude Opus 5 or DeepSeek V4-Flash cheaper for output?
DeepSeek V4-Flash is cheaper at $0.28 per million output tokens, against $25 for Claude Opus 5 — roughly 89× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; DeepSeek V4-Flash has tiered pricing: Current list is $0.14/$0.28 per million tokens (cache miss / output) until 2026-08-16 16:00 UTC. From then, official peak/off-peak rates: off-peak $0.22/$0.66, peak $0.44/$1.32 (cache miss / output). Peak hours are 01:00–04:00 and 06:00–10:00 UTC.
Which has the larger context window, Claude Opus 5 or DeepSeek V4-Flash?
Both accept about 1M tokens of context, so document length will not decide between them.
Do Claude Opus 5 and DeepSeek V4-Flash support the same reasoning levels?
Claude Opus 5 exposes low, medium, high, xhigh, max, while DeepSeek V4-Flash exposes low, high, max.
Should I use Claude Opus 5 or DeepSeek V4-Flash?
Claude Opus 5 is the frontier tier and DeepSeek V4-Flash the budget tier. The useful question is whether your hardest task actually fails on the cheaper one — most production volume such as classification, extraction and summarisation does not.
Can I self-host Claude Opus 5 or DeepSeek V4-Flash?
DeepSeek V4-Flash publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Claude Opus 5 is a closed model whose supported access paths are controlled by its provider.
Next step
Choosing between them
Tier and workload decide this more reliably than a leaderboard position does.
If both sit in the same tier, the decision usually comes down to context window and output price rather than headline capability — output tokens dominate real bills.
If one is a step up within the same provider, the useful question is whether your hardest task actually fails on the cheaper tier. Most production volume — classification, extraction, summarization — does not.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Muse Code, or Lovable? Compare agentic harnesses · Latest releases.