DeepSeek V4 Pro vs gpt-oss-20b
At a Glance
| Compare |  DeepSeek V4 ProDeepSeek |  gpt-oss-20bOpenAI |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #28 of 4655.3 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 36.9–70.2 | UnrankedNot in the 46-model eligible cohort |
| CostLower is better · Published-token output estimate | #10 of 44$0.054 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.5 | #12 of 3858.4 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 49.2–65.9 | UnrankedNot in the 38-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.66DeepSeek ↗ · Sep 2, 2026 | $0.018Openrouter ↗ · Sep 23, 2026 |
| Output priceFrom · USD / 1M tokens | $1.5441Openrouter ↗ · Aug 28, 2026 | $0.090Openrouter ↗ · Sep 23, 2026 |
| Context windowMaximum documented tokens | 1,049K | 131K |
| 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 | DeepSeek-V4-Pro | gpt-oss-20b |
|---|---|---|
| LMArena Text Arenatext-2026-09-13-d25aabda0010 · arena_rating · leader | 1,450.63100% of row best · rating · deepseek-v4-pro; 95% CI [1446.64622706, 1454.61308427]; votes 54130; rank 43 | 1,287.3289% of row best · rating · gpt-oss-20b; 95% CI [1280.92242279, 1293.71473349]; votes 10393; rank 246 |
| Overall ResultCounted from the protocol-matched rows above | 1 benchmark winNo overall winner | 0 benchmark winsNo overall winner |
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 | DeepSeek-V4-Pro | gpt-oss-20b |
|---|---|---|
| Developer | DeepSeek | OpenAI |
| Family | Deepseek V4 Pro | Gpt Oss |
| Model | DeepSeek-V4-Pro | gpt-oss-20b |
| Version | DeepSeek-V4-Pro | gpt-oss-20b |
| Lifecycle | active | active |
| Released | 2026-04-24 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Text |
| Context window | 1,049K | 131K |
| Total parameters | 1.6T | 20.9B |
| Active parameters | 49B | 3.6B |
| License | mit | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | DeepSeek (Standard), Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Deepinfra (Standard), Groq (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Serverless, Standard) |
| Capabilities | chat, generation, reasoning | chat, generation, reasoning, tools |
DeepSeek V4 Pro Capabilities
gpt-oss-20b Capabilities
Related Comparisons
All text comparisons →| A | Pair | B | Context |
|---|---|---|---|
DeepSeek-V3.2DeepSeek | vs | DeepSeek-V4-ProDeepSeek | family variantstext |
DeepSeek-V4-ProDeepSeek | vs | GPT-6 AstraOpenAI | cross-developer peerstext |
Claude Fable 5.1Anthropic | vs | DeepSeek-V4-ProDeepSeek | cross-developer peerstext |
DeepSeek-V4-ProDeepSeek | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
DeepSeek-V4-ProDeepSeek | vs | DeepSeek-V4.1-FlashDeepSeek | family variantstext |
DeepSeek-V4-ProDeepSeek | vs | Grok 4.6xAI | cross-developer peerstext |
DeepSeek-V4-ProDeepSeek | vs |  Qwen3.8-MaxQwen | cross-developer peerstext |
DeepSeek-V4-ProDeepSeek | vs |  Kimi-K3Moonshot AI | cross-developer peerstext |
 MiniMax-M3MiniMax | vs | DeepSeek-V4-ProDeepSeek | cross-developer peerstext |
DeepSeek-V4-ProDeepSeek | vs |  GLM-5.3Z.ai | cross-developer peerstext |
DeepSeek-V4-ProDeepSeek | vs |  Hy4 previewTencent | cross-developer peerstext |
Seed 2.1 ProByteDance Seed | vs | DeepSeek-V4-ProDeepSeek | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
DeepSeek V4 Pro vs gpt-oss-20b FAQs
Is DeepSeek V4 Pro or gpt-oss-20b better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both DeepSeek V4 Pro and gpt-oss-20b, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, DeepSeek V4 Pro or gpt-oss-20b?+
DeepSeek V4 Pro is $0.66 and gpt-oss-20b is $0.018 per million tokens, so gpt-oss-20b is cheaper on this metric. DeepSeek V4 Pro is $1.5441 and gpt-oss-20b is $0.090 per million tokens, so gpt-oss-20b is cheaper on this metric.
Which has a larger context window, DeepSeek V4 Pro or gpt-oss-20b?+
DeepSeek V4 Pro has the larger sourced context window. DeepSeek V4 Pro supports 1,049K and gpt-oss-20b supports 131K.
Which performs better in benchmarks, DeepSeek V4 Pro or gpt-oss-20b?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can DeepSeek V4 Pro or gpt-oss-20b be self-hosted?+
Both models have the same recorded self-hosting status: supported. DeepSeek V4 Pro is open weight; gpt-oss-20b is open weight.
Can DeepSeek V4 Pro and gpt-oss-20b understand images?+
DeepSeek V4 Pro is not documented with image input; gpt-oss-20b is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, DeepSeek V4 Pro or gpt-oss-20b?+
Neither has a larger sourced maximum output. DeepSeek V4 Pro is — and gpt-oss-20b is —.
Do DeepSeek V4 Pro and gpt-oss-20b support reasoning and tool use?+
DeepSeek V4 Pro: reasoning. gpt-oss-20b: reasoning and tool calling. Feature support does not establish relative quality.
Which is available from more inference providers, DeepSeek V4 Pro or gpt-oss-20b?+
DeepSeek V4 Pro has 6 sourced provider routes; gpt-oss-20b has 5, so DeepSeek V4 Pro has broader tracked availability.
Which offers better value, DeepSeek V4 Pro or gpt-oss-20b?+
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.