Friendli
5 indexed models
- Headquarters
United States- Server regions
- N/a
- Model types
- 5 text
Same-model provider benchmark
Friendli vs Venice: LLM provider comparison
Compare Friendli and Venice on 5 exact shared text models. ProviderBench keeps speed, price, and catalog coverage separate so naturally faster model catalogs cannot distort the result.
Venice
29 indexed models
- Headquarters
- United States
- Server regions
- United States
- Model types
- 29 text
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 | Friendli | Venice |
|---|---|---|
| Typical 500-token response | 5.41 s | 14.61 s |
| Typical response start | 0.57 s | 1.16 s |
| Typical output speed | 112.0 tok/s | 38.0 tok/s |
| Blended token price | $1.3267 / 1M | $1.2533 / 1M |
| Typical route uptime | 99.08% | 96.94% |
Visual comparison
Price and performance charts
Estimated seconds using recent median response-start and output-speed data. Lower is better.
Friendli has the lower typical same-model response ratio across 5 measured models.
USD per 1 million tokens using a 1,000-input/500-output mix. Lower is better.
Venice has the lower typical price ratio across 5 priced shared models.
| Model | Friendli | Venice |
|---|---|---|
 GLM 5.2Winner · Friendli z-ai/glm-5.2 | Friendli
| Venice
|
GLM 5.1Winner · Friendli z-ai/glm-5.1 | Friendli
| Venice
|
 MiniMax M2.5Winner · Friendli minimax/minimax-m2.5 | Friendli
| Venice
|
 DeepSeek V3.2Winner · Friendli deepseek/deepseek-v3.2 | Friendli
| Venice
|
 Qwen3 235B A22B Instruct 2507Winner · Friendli qwen/qwen3-235b-a22b-2507 | Friendli
| Venice
|
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.
Friendli vs Venice analysis
How Friendli and Venice compare for AI inference
Friendli and Venice share 5 indexed text models, including GLM 5.2, GLM 5.1, MiniMax M2.5, DeepSeek V3.2, Qwen3 235B A22B Instruct 2507. Friendli has the stronger typical response-time result on the directly measured set.
Same-model speed evidence
5 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
5 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
Friendli has 5 indexed models and lists no published server regions; Venice has 29 models and lists 1 region. 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 Friendli and Venice.
