NovitaAI
66 indexed models
- Headquarters
United States
- Server regions
- N/a
- Model types
- 66 text
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Same-model provider benchmark
Compare NovitaAI and Parasail on 22 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.
66 indexed models
35 indexed models
At a glance
There is no overall score. Each winner answers one specific question using only directly comparable data.
| Metric | NovitaAI | Parasail |
|---|---|---|
| Typical 500-token response | 18.71 s | 12.94 s |
| Typical response start | 1.52 s | 0.69 s |
| Typical output speed | 30.5 tok/s | 42.0 tok/s |
| Blended token price | $0.8071 / 1M | $0.8709 / 1M |
| Typical route uptime | 99.36% | 98.88% |
Visual comparison
Estimated seconds using recent median response-start and output-speed data. Lower is better.
Parasail has the lower typical same-model response ratio across 22 measured models.
USD per 1 million tokens using a 1,000-input/500-output mix. Lower is better.
NovitaAI has the lower typical price ratio across 22 priced shared models.
| Model | NovitaAI | Parasail |
|---|---|---|
GLM 5.2Winner · Parasail z-ai/glm-5.2 | NovitaAI
| Parasail
|
Kimi K2.7 CodeWinner · Parasail moonshotai/kimi-k2.7-code | NovitaAI
| Parasail
|
MiniMax M3Winner · Parasail minimax/minimax-m3 | NovitaAI
| Parasail
|
DeepSeek V4 ProWinner · NovitaAI deepseek/deepseek-v4-pro | NovitaAI
| Parasail
|
DeepSeek V4 FlashWinner · Parasail deepseek/deepseek-v4-flash | NovitaAI
| Parasail
|
MiMo-V2.5Winner · NovitaAI xiaomi/mimo-v2.5 | NovitaAI
| Parasail
|
Kimi K2.6Winner · Parasail moonshotai/kimi-k2.6 | NovitaAI
| Parasail
|
GLM 5.1Winner · Parasail z-ai/glm-5.1 | NovitaAI
| Parasail
|
Gemma 4 26B A4BWinner · Parasail google/gemma-4-26b-a4b-it | NovitaAI
| Parasail
|
Gemma 4 31BWinner · Parasail google/gemma-4-31b-it | NovitaAI
| Parasail
|
Qwen3.5 397B A17BWinner · Parasail qwen/qwen3.5-397b-a17b | NovitaAI
| Parasail
|
MiniMax M2.5Winner · Parasail minimax/minimax-m2.5 | NovitaAI
| Parasail
|
GLM 5Winner · Parasail z-ai/glm-5 | NovitaAI
| Parasail
|
Qwen3 Coder NextWinner · Parasail qwen/qwen3-coder-next | NovitaAI
| Parasail
|
Qwen3 VL 235B A22B InstructWinner · Parasail qwen/qwen3-vl-235b-a22b-instruct | NovitaAI
| Parasail
|
Qwen3 Next 80B A3B InstructWinner · Parasail qwen/qwen3-next-80b-a3b-instruct | NovitaAI
| Parasail
|
gpt-oss-120bWinner · NovitaAI openai/gpt-oss-120b | NovitaAI
| Parasail
|
gpt-oss-20bWinner · NovitaAI openai/gpt-oss-20b | NovitaAI
| Parasail
|
Qwen3 235B A22B Instruct 2507Winner · NovitaAI qwen/qwen3-235b-a22b-2507 | NovitaAI
| Parasail
|
Llama 4 MaverickWinner · Parasail meta-llama/llama-4-maverick | NovitaAI
| Parasail
|
Gemma 3 27BWinner · Parasail google/gemma-3-27b-it | NovitaAI
| Parasail
|
Llama 3.3 70B InstructWinner · NovitaAI meta-llama/llama-3.3-70b-instruct | NovitaAI
| Parasail
|
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.
NovitaAI vs Parasail analysis
NovitaAI and Parasail share 22 indexed text models, including GLM 5.2, Kimi K2.7 Code, MiniMax M3, DeepSeek V4 Pro, DeepSeek V4 Flash. Parasail has the stronger typical response-time result on the directly measured set.
22 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.
22 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.
NovitaAI has 66 indexed models and lists no published server regions; Parasail has 35 models and lists no regions. Verify data residency, privacy terms, limits, and production latency directly before choosing.
Related same-model benchmarks
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