llmreference

DeepSeek V3 vs gpt-oss-120b

DeepSeek V3 (2024) and gpt-oss-120b (2025) are compact production models from DeepSeek and OpenAI. DeepSeek V3 ships a 64k-token context window, while gpt-oss-120b ships a 131K-token context window. On pricing, gpt-oss-120b costs $0.04/1M input tokens versus $0.1/1M for the alternative. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing.

gpt-oss-120b is ~156% cheaper at $0.04/1M; pay for DeepSeek V3 only for provider fit.

Decision scorecard

Local evidence first
SignalDeepSeek V3gpt-oss-120b
Decision fitCoding, Agents, and ClassificationRAG, Agents, and Long context
Context window64k131K
Cheapest output$0.3/1M tokens$0.18/1M tokens
Provider routes12 tracked7 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose DeepSeek V3 when...
  • DeepSeek V3 has broader tracked provider coverage for fallback and procurement flexibility.
  • Local decision data tags DeepSeek V3 for Coding, Agents, and Classification.
Choose gpt-oss-120b when...
  • gpt-oss-120b has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • gpt-oss-120b has the lower cheapest tracked output price at $0.18/1M tokens.
  • 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.

Lower estimate gpt-oss-120b

DeepSeek V3

$155

Cheapest tracked route: Bitdeer AI

gpt-oss-120b

$76.20

Cheapest tracked route: OpenRouter

Estimated monthly gap: $78.80. Batch, cache, and negotiated pricing are excluded from this local estimate.

Switch friction

DeepSeek V3 -> gpt-oss-120b
  • Provider overlap exists on OpenRouter, Together AI, and Fireworks AI; start route-level A/B tests there.
  • gpt-oss-120b is $0.12/1M tokens lower on cheapest tracked output pricing before cache, batch, or negotiated discounts.
gpt-oss-120b -> DeepSeek V3
  • Provider overlap exists on Fireworks AI, OpenRouter, and NVIDIA NIM; start route-level A/B tests there.
  • DeepSeek V3 is $0.12/1M tokens higher on cheapest tracked output pricing, so quality gains need to justify the spend.

Specs

Specification
Released2024-12-262025-08-05
Context window64k131K
Parameters671B120B
Architecturemixture of expertsdecoder only
LicenseOpen SourceOpen Source
Knowledge cutoff2024-042025-08

Pricing and availability

Pricing attributeDeepSeek V3gpt-oss-120b
Input price$0.1/1M tokens$0.04/1M tokens
Output price$0.3/1M tokens$0.18/1M tokens
Providers

Capabilities

CapabilityDeepSeek V3gpt-oss-120b
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
Code executionNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint is close: both models cover function calling, tool use, and structured outputs. That makes context budget, benchmark fit, and provider maturity more important than a simple checklist. If your application depends on one integration detail, verify it against the provider route you plan to use, not just the base model listing.

For cost, DeepSeek V3 lists $0.1/1M input and $0.3/1M 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 $0.08 per million blended tokens. Availability is 12 providers versus 7, so concentration risk also matters.

Choose DeepSeek V3 when provider fit and broader provider choice are central to the workload. Choose gpt-oss-120b when long-context analysis, larger context windows, and lower input-token cost are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Which has a larger context window, DeepSeek V3 or gpt-oss-120b?

gpt-oss-120b supports 131K tokens, while DeepSeek V3 supports 64k 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 or gpt-oss-120b?

gpt-oss-120b is cheaper on tracked token pricing. DeepSeek V3 costs $0.1/1M input and $0.3/1M 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 or gpt-oss-120b open source?

DeepSeek V3 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 or gpt-oss-120b?

Both DeepSeek V3 and gpt-oss-120b expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for tool use, DeepSeek V3 or gpt-oss-120b?

Both DeepSeek V3 and gpt-oss-120b expose tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run DeepSeek V3 and gpt-oss-120b?

DeepSeek V3 is available on DeepInfra, Fireworks AI, DeepSeek Platform, Microsoft Foundry, and OpenRouter. 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.

Continue comparing

Last reviewed: 2026-05-16. Data sourced from public model cards and provider documentation.