DBRX vs GPT-5 nano
A complete head-to-head: pricing, context window, benchmarks, modality coverage, and openness, with a programmatic verdict synthesized from the underlying data.
Updated
DBRX specs · GPT-5 nano specs- PriceGPT-5 nano
GPT-5 nano publishes pricing ($0.40 / 1M output tokens) while DBRX does not.
- Context windowGPT-5 nano
GPT-5 nano accepts 400K tokens vs 32K, 12.5× the room for long documents and codebases.
- BenchmarksTie
No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores.
- ModalitiesGPT-5 nano
GPT-5 nano supports 2 modalities (text, vision) vs 1 for DBRX.
- OpennessDBRX
DBRX ships open weights (Databricks Open Model License); GPT-5 nano is API-only.
On balance GPT-5 nano edges ahead, winning 3 of 5 categories against DBRX's 1. GPT-5 nano publishes pricing ($0.40 / 1M output tokens) while DBRX does not. GPT-5 nano accepts 400K tokens vs 32K, 12.5× the room for long documents and codebases.
No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores. They differ in modality coverage, DBRX handles text while GPT-5 nano handles text, vision, which can be the deciding factor before you even look at benchmarks. DBRX ships open weights (Databricks Open Model License); GPT-5 nano is API-only.
GPT-5 nano is the newer of the two, released 17 months after DBRX, which usually means a more recent knowledge cutoff and updated safety post-training. DBRX is usually picked for enterprise llm and sql generation workloads, while GPT-5 nano sees more deployments in cheapest llm and fastest llm. If pricing matters more than every last benchmark point, run the numbers in the calculator below before committing.
Side-by-side specs
| Spec | DBRX | GPT-5 nano |
|---|---|---|
| Provider | Other | OpenAI |
| Released | Mar 2024 | Aug 2025 |
| Modalities | text | text, vision |
| Context window | 32K tokens | 400K tokens |
| Max output | , | 128K tokens |
| Input · 1M | Pricing not published | $0.050 / 1M tokens |
| Output · 1M | Pricing not published | $0.40 / 1M tokens |
| Knowledge cutoff | , | 2024-09 |
| Open weights | Yes (Databricks Open Model License) | No |
| API available | Yes | Yes |
Pricing at scale
What you'd actually pay at typical workloads. Numbers come from each model's published per-million-token rates.
- Light usage, 100k in / 50k out per day, vs $0.750
- Heavy usage, 1M in / 500k out per day, vs $7.50
- RAG workload, 5M in / 200k out per day, vs $9.90
Light usage, 100k in / 50k out per day: pricing not directly comparable (one or both models are missing public per-token rates). Heavy usage, 1M in / 500k out per day: pricing not directly comparable (one or both models are missing public per-token rates). RAG workload, 5M in / 200k out per day: pricing not directly comparable (one or both models are missing public per-token rates).
Estimated spend for the listed models at your usage. Numbers are derived from each model's published per-million-token rates.
- DBRXPricing unavailable
- GPT-5 nano$0.025
Benchmarks compared
Only sourced numbers. Where a benchmark is missing for one model we show the available value rather than fabricating the other.
- MMLU73.7
DBRX fits when…
- Databricks-native
- Tuned for enterprise SQL/code
- Self-hosting and on-prem requirements, open weights (Databricks Open Model License).
GPT-5 nano fits when…
- Lowest-cost OpenAI model with vision support
- Fast P99 latency
- Good enough for routing and classification
- Long-context tasks, handles 400K tokens vs 32K for DBRX.
- Multimodal needs covering vision.
Consider Yi-Lightning
01.AI's API-tier Chinese-leaning model, strong on Chinese benchmarks at competitive pricing.
Frequently asked
Is DBRX or GPT-5 nano cheaper?
Per-token pricing isn't published for at least one of these models, check each model's spec page for current rates.Which has the larger context window?
GPT-5 nano accepts 400K tokens vs 32K for DBRX.Is DBRX or GPT-5 nano better for coding?
Both DBRX and GPT-5 nano are competitive on coding benchmarks. See each model's individual spec page for HumanEval and SWE-bench scores where published. For an opinionated pick, consult our Best LLM for Coding ranking.Are either of these models open source?
DBRX ships open weights (Databricks Open Model License). GPT-5 nano is API-only.When were DBRX and GPT-5 nano released?
DBRX was released by Other on 2024-03-27. GPT-5 nano was released by OpenAI on 2025-08-07.
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