DeepSeek V3.2 vs gpt-oss-120b
DeepSeek V3.2 (2025) and gpt-oss-120b (2025) are general-purpose language models from DeepSeek and OpenAI. DeepSeek V3.2 ships a 160K-token context window, while gpt-oss-120b ships a 131K-token context window. On Google-Proof Q&A, DeepSeek V3.2 leads by 5.8 pts. On pricing, gpt-oss-120b costs $0.04/1M input tokens versus $0.25/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit.
gpt-oss-120b is ~546% cheaper at $0.04/1M; pay for DeepSeek V3.2 only for coding workflow support.
Decision scorecard
Local evidence first| Signal | DeepSeek V3.2 | gpt-oss-120b |
|---|---|---|
| Decision fit | Coding, RAG, and Agents | RAG, Agents, and Long context |
| Context window | 160K | 131K |
| Cheapest output | $0.38/1M tokens | $0.18/1M tokens |
| Provider routes | 5 tracked | 7 tracked |
| Shared benchmarks | Google-Proof Q&A leader | 1 rows |
Decision tradeoffs
- DeepSeek V3.2 leads the largest shared benchmark signal on Google-Proof Q&A by 5.8 points.
- DeepSeek V3.2 has the larger context window for long prompts, retrieval packs, or transcript analysis.
- DeepSeek V3.2 uniquely exposes Code execution in local model data.
- Local decision data tags DeepSeek V3.2 for Coding, RAG, and Agents.
- gpt-oss-120b has the lower cheapest tracked output price at $0.18/1M tokens.
- gpt-oss-120b has broader tracked provider coverage for fallback and procurement flexibility.
- gpt-oss-120b uniquely exposes Function calling and Tool use in local model data.
- Local decision data tags gpt-oss-120b for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output prices on this page.
DeepSeek V3.2
$296
Cheapest tracked route: OpenRouter
gpt-oss-120b
$76.20
Cheapest tracked route: OpenRouter
Estimated monthly gap: $220. Batch, cache, and negotiated pricing are excluded from this local estimate.
Switch friction
- Provider overlap exists on OpenRouter, Fireworks AI, and NVIDIA NIM; start route-level A/B tests there.
- gpt-oss-120b is $0.2/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
- Check replacement coverage for Code execution before moving production traffic.
- gpt-oss-120b adds Function calling and Tool use in local capability data.
- Provider overlap exists on Fireworks AI, NVIDIA NIM, and OpenRouter; start route-level A/B tests there.
- DeepSeek V3.2 is $0.2/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.
- Check replacement coverage for Function calling and Tool use before moving production traffic.
- DeepSeek V3.2 adds Code execution in local capability data.
Specs
| Specification | ||
|---|---|---|
| Released | 2025-01-01 | 2025-08-05 |
| Context window | 160K | 131K |
| Parameters | 671B | 120B |
| Architecture | decoder only | decoder only |
| License | Open Source | Open Source |
| Knowledge cutoff | - | 2025-08 |
Pricing and availability
| Pricing attribute | DeepSeek V3.2 | gpt-oss-120b |
|---|---|---|
| Input price | $0.25/1M tokens | $0.04/1M tokens |
| Output price | $0.38/1M tokens | $0.18/1M tokens |
| Providers |
Capabilities
| Capability | DeepSeek V3.2 | gpt-oss-120b |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | No |
| Function calling | No | Yes |
| Tool use | No | Yes |
| Structured outputs | Yes | Yes |
| Code execution | Yes | No |
Benchmarks
| Benchmark | DeepSeek V3.2 | gpt-oss-120b |
|---|---|---|
| Google-Proof Q&A | 84.0 | 78.2 |
Deep dive
On shared benchmark coverage, Google-Proof Q&A has DeepSeek V3.2 at 84 and gpt-oss-120b at 78.2, with DeepSeek V3.2 ahead by 5.8 points. The largest visible gap is 5.8 points on Google-Proof Q&A, which matters most when that benchmark mirrors your workload. Treat isolated benchmark wins as directional, because provider routing, prompt style, and tool access can move real application results.
The capability footprint differs most on function calling: gpt-oss-120b, tool use: gpt-oss-120b, and code execution: DeepSeek V3.2. Both models share structured outputs, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.
For cost, DeepSeek V3.2 lists $0.25/1M input and $0.38/1M output tokens, while gpt-oss-120b lists $0.04/1M input and $0.18/1M output tokens on the cheapest tracked provider. A 70/30 input-output blend puts gpt-oss-120b lower by about $0.21 per million blended tokens. Availability is 5 providers versus 7, so concentration risk also matters.
Choose DeepSeek V3.2 when coding workflow support and larger context windows are central to the workload. Choose gpt-oss-120b when provider fit, lower input-token cost, and broader provider choice are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship.
FAQ
Which has a larger context window, DeepSeek V3.2 or gpt-oss-120b?
DeepSeek V3.2 supports 160K tokens, while gpt-oss-120b supports 131K tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.
Which is cheaper, DeepSeek V3.2 or gpt-oss-120b?
gpt-oss-120b is cheaper on tracked token pricing. DeepSeek V3.2 costs $0.25/1M input and $0.38/1M output tokens. gpt-oss-120b costs $0.04/1M input and $0.18/1M output tokens. Provider discounts or batch pricing can still change the final bill.
Is DeepSeek V3.2 or gpt-oss-120b open source?
DeepSeek V3.2 is listed under Open Source. gpt-oss-120b is listed under Open Source. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.
Which is better for function calling, DeepSeek V3.2 or gpt-oss-120b?
gpt-oss-120b has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Which is better for tool use, DeepSeek V3.2 or gpt-oss-120b?
gpt-oss-120b has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.
Where can I run DeepSeek V3.2 and gpt-oss-120b?
DeepSeek V3.2 is available on Fireworks AI, NVIDIA NIM, AWS Bedrock, OpenRouter, and Microsoft Foundry. gpt-oss-120b is available on OpenRouter, Together AI, Fireworks AI, GCP Vertex AI, and NVIDIA NIM. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-19. Data sourced from public model cards and provider documentation.