DekaLLM
7 indexed models
- Headquarters
Indonesia
- Server regions
Indonesia
- Model types
- 7 text
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Same-model provider benchmark
Compare DekaLLM and Nebius on 3 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.
7 indexed models
13 indexed models
At a glance
There is no overall score. Each winner answers one specific question using only directly comparable data.
| Metric | DekaLLM | Nebius |
|---|---|---|
| Typical 500-token response | 17.74 s | 6.62 s |
| Typical response start | 1.07 s | 0.67 s |
| Typical output speed | 30.0 tok/s | 84.0 tok/s |
| Blended token price | $0.1478 / 1M | $0.3222 / 1M |
| Typical route uptime | 98.29% | 99.41% |
Visual comparison
Estimated seconds using recent median response-start and output-speed data. Lower is better.
Nebius has the lower typical same-model response ratio across 3 measured models.
USD per 1 million tokens using a 1,000-input/500-output mix. Lower is better.
DekaLLM has the lower typical price ratio across 3 priced shared models.
| Model | DekaLLM | Nebius |
|---|---|---|
Nemotron 3 SuperWinner · Nebius nvidia/nemotron-3-super-120b-a12b | DekaLLM
| Nebius
|
gpt-oss-120bWinner · DekaLLM openai/gpt-oss-120b | DekaLLM
| Nebius
|
Qwen3 30B A3B Instruct 2507Winner · Nebius qwen/qwen3-30b-a3b-instruct-2507 | DekaLLM
| Nebius
|
A per-model winner combines blended price and estimated 500-token response time with equal proportional weight. Ties and rows missing either measurement receive no badge. Comparison data calculated . Values use one deterministic route per provider and model; missing measurements remain visible as N/a.
DekaLLM vs Nebius analysis
DekaLLM and Nebius share 3 indexed text models, including Nemotron 3 Super, gpt-oss-120b, Qwen3 30B A3B Instruct 2507. Nebius has the stronger typical response-time result on the directly measured set.
3 shared models currently have complete response-start and output-speed measurements on both providers. The speed comparison uses per-model ratios before taking the median, so naturally faster model catalogs do not improve the result.
3 shared models have complete input and output prices on both providers. Prices use the same 1,000-input/500-output-token mix and are normalized to one million tokens for readability.
DekaLLM has 7 indexed models and lists 1 published server region; Nebius has 13 models and lists no regions. Verify data residency, privacy terms, limits, and production latency directly before choosing.
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