Ambient
3 indexed models
- Headquarters
- N/a
- Server regions
- N/a
- Model types
- 3 text
Same-model provider benchmark
Ambient vs DeepInfra: LLM provider comparison
Compare Ambient and DeepInfra on 3 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.
DeepInfra
87 indexed models
- Headquarters
United States- Server regions
- N/a
- Model types
- 67 text, 15 embeddings, 5 speech
At a glance
Metric winners
There is no overall score. Each winner answers one specific question using only directly comparable data.
Shared-model benchmark summary
| Metric | Ambient | DeepInfra |
|---|---|---|
| Typical 500-token response | 12.46 s | 15.92 s |
| Typical response start | 0.83 s | 0.70 s |
| Typical output speed | 43.0 tok/s | 33.0 tok/s |
| Blended token price | $1.4387 / 1M | $1.2656 / 1M |
| Typical route uptime | 99.74% | 100.00% |
Visual comparison
Price and performance charts
DeepInfraEstimated seconds using recent median response-start and output-speed data. Lower is better.
Ambient 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.
DeepInfra has the lower typical price ratio across 3 priced shared models.
| Model | Ambient | DeepInfra |
|---|---|---|
 GLM 5.2Winner · Ambient z-ai/glm-5.2 | Ambient
| DeepInfra
|
 Kimi K2.7 CodeWinner · Ambient moonshotai/kimi-k2.7-code | Ambient
| DeepInfra
|
 Step 3.7 FlashWinner · DeepInfra stepfun/step-3.7-flash | Ambient
| DeepInfra
|
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.
Ambient vs DeepInfra analysis
How Ambient and DeepInfra compare for AI inference
Ambient and DeepInfra share 3 indexed text models, including GLM 5.2, Kimi K2.7 Code, Step 3.7 Flash. Ambient has the stronger typical response-time result on the directly measured set.
Same-model speed evidence
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.
Token pricing on one workload
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.
Catalog and deployment differences
Ambient has 3 indexed models and lists no published server regions; DeepInfra has 87 models and lists no regions. Verify data residency, privacy terms, limits, and production latency directly before choosing.
Related same-model benchmarks
Compare with other providers
Explore qualified alternatives with the most shared measured models. Recommendations include comparisons for both Ambient and DeepInfra.
