Claude Sonnet 5 vs DeepSeek V4 Flash
At a Glance
| Compare | Claude Sonnet 5Anthropic | DeepSeek V4 FlashDeepSeek |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #26 of 4660.1 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 40.0–73.4 | UnrankedNot in the 46-model eligible cohort |
| CostLower is better · Published-token output estimate | #29 of 44$0.194 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.5 | #30 of 3847.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 37.4–54.0 | UnrankedNot in the 38-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $2.00Anthropic ↗ · Sep 3, 2026 | $0.0868Openrouter ↗ · Aug 28, 2026 |
| Output priceFrom · USD / 1M tokens | $10.00Anthropic ↗ · Sep 3, 2026 | $0.1736Openrouter ↗ · Aug 28, 2026 |
| Context windowMaximum documented tokens | 1,000K | 1,049K |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 28, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
| Benchmark | Claude Sonnet 5 | DeepSeek-V4-Flash |
|---|---|---|
| LMArena Agent Arenaagent-2026-09-15-d25aabda0010 · outcome_score · leader | 5.97100% of row best · score · Claude Sonnet 5 (High); 95% CI [4.35064977, 7.58850066]; sessions 30631; observations 3176952; rank 9 | 1.8096% of row best · score · Deepseek V4 Flash (High) (20260731); 95% CI [1.06225523, 2.53222539]; sessions 64482; observations 6405377; rank 22 |
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,442.15100% of row best · rating · claude-sonnet-5-high; 95% CI [1437.57467941, 1446.71829948]; votes 35301; rank 62 | 1,431.7999% of row best · rating · deepseek-v4-flash; 95% CI [1427.66110387, 1435.91557810]; votes 48887; rank 83 |
| LiveBench2026-06-25 · overall · leader | 80.01100% of row best · percent · claude-sonnet-5-xhigh-effort · 19,428 output tokens / case | 69.6787% of row best · percent · deepseek-v4-flash · 34,434 output tokens / case |
| ToneBench2026-09-11-10-task-4ef099199c9c · overall_score · unverified | 86.51100% of row best · points · Claude Sonnet 5 (max effort) · 71,003 output tokens / case | 78.0090% of row best · points · DeepSeek V4 Flash (xhigh) · 12,709 output tokens / case |
| Overall ResultCounted from the protocol-matched rows above | 3 benchmark winsOverall lead | 0 benchmark wins |
Third-party benchmark Only like-for-like primary-publisher results are shown; raw scores, relative scores, configuration, and token spend remain visible.
Side-by-Side Facts
| Field | Claude Sonnet 5 | DeepSeek-V4-Flash |
|---|---|---|
| Developer | Anthropic | DeepSeek |
| Family | Claude 5 | Deepseek V4 Flash |
| Model | Claude Sonnet 5 | DeepSeek-V4-Flash |
| Version | Claude Sonnet 5 | DeepSeek-V4-Flash |
| Lifecycle | active | retired |
| Released | 2026-06-30 | 2026-04-24 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Text |
| Context window | 1,000K | 1,049K |
| Total parameters | Unknown | 290.9B |
| Active parameters | Unknown | 13B |
| License | Unknown | mit |
| Open weights | No | Yes |
| API available | Yes | Yes |
| Self-hostable | No | Yes |
| Provider access | Anthropic (Standard), Deepinfra (Standard), Openrouter (Standard) | DeepSeek (Standard), Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning |
Claude Sonnet 5 Capabilities
DeepSeek V4 Flash Capabilities
Primary Evidence
Sources and Freshness
Questions
Claude Sonnet 5 vs DeepSeek V4 Flash FAQs
Is Claude Sonnet 5 or DeepSeek V4 Flash better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Sonnet 5 and DeepSeek V4 Flash, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Sonnet 5 or DeepSeek V4 Flash?+
Claude Sonnet 5 is $2.00 and DeepSeek V4 Flash is $0.0868 per million tokens, so DeepSeek V4 Flash is cheaper on this metric. Claude Sonnet 5 is $10.00 and DeepSeek V4 Flash is $0.1736 per million tokens, so DeepSeek V4 Flash is cheaper on this metric.
Which has a larger context window, Claude Sonnet 5 or DeepSeek V4 Flash?+
DeepSeek V4 Flash has the larger sourced context window. Claude Sonnet 5 supports 1,000K and DeepSeek V4 Flash supports 1,049K.
Which performs better in benchmarks, Claude Sonnet 5 or DeepSeek V4 Flash?+
Claude Sonnet 5 leads the current overall benchmark count. The result uses 3 protocol-matched benchmarks from 2 publishers; it is not a universal quality score.
Can Claude Sonnet 5 or DeepSeek V4 Flash be self-hosted?+
DeepSeek V4 Flash is the only model in this pair currently marked as self-hostable. Claude Sonnet 5 is not marked open weight; DeepSeek V4 Flash is open weight.
Can Claude Sonnet 5 and DeepSeek V4 Flash understand images?+
Claude Sonnet 5 is documented with image input; DeepSeek V4 Flash is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Sonnet 5 or DeepSeek V4 Flash?+
Neither has a larger sourced maximum output. Claude Sonnet 5 is 128K and DeepSeek V4 Flash is —.
Do Claude Sonnet 5 and DeepSeek V4 Flash support reasoning and tool use?+
Claude Sonnet 5: reasoning, tool calling, and image input. DeepSeek V4 Flash: reasoning. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Sonnet 5 or DeepSeek V4 Flash?+
Claude Sonnet 5 has 3 sourced provider routes; DeepSeek V4 Flash has 5, so DeepSeek V4 Flash has broader tracked availability.
Which offers better value, Claude Sonnet 5 or DeepSeek V4 Flash?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.