inferenstack — the market read on AI inference · last observation 2026-09-20. See the boards
Provider intelligence

Who's premium, who's cheap

Where each provider sits on price across the models it actually competes on (percentile 0 = always cheapest, 100 = always priciest). A provider consistently in the top quartile is selling something other than price — latency, compliance, brand.

Prices vendor-claimed · positions and percentiles are computed from them.

not yet measuredReliability, latency & uptime

We don't run latency/uptime/TTFT probes yet, so we have no measured reliability data — and we won't invent an SLA score from vendor marketing. When probes ship, a measured reliability axis appears here.

Build dependency: provider probe infrastructure (Phase 6)

126 providers
ProviderClassModelsPrice positionTop-quartileOpen wtsCache
Privatemode AIrelay / router11(8 comp.)
92
88%100%100%
GreenPTrelay / router40(24 comp.)
84
88%95%38%
Infomaniakrelay / router10(7 comp.)
83
71%90%0%
above.devrelay / router9(8 comp.)
78
63%89%100%
Venice AI—107(89 comp.)
75
67%46%83%
Tinfoilrelay / router10(8 comp.)
74
75%100%50%
Berget.AIrelay / router6(6 comp.)
73
67%100%0%
Alibabafirst-party lab56(54 comp.)
71
52%45%17%
STACKITrelay / router8(5 comp.)
69
60%100%0%
Scalewayrelay / router15(11 comp.)
69
64%93%9%
Regolo AIrelay / router18(11 comp.)
68
64%78%0%
Charm Hyperrelay / router34(23 comp.)
67
43%74%100%
Incorelay / router7(7 comp.)
65
57%100%0%
Waferrelay / router5(5 comp.)
62
40%100%100%
evrocrelay / router16(12 comp.)
61
58%94%0%
Mixlayerrelay / router5(5 comp.)
60
20%100%0%
Cortecsrelay / router107(97 comp.)
59
49%56%68%
Meliousrelay / router15(15 comp.)
56
40%93%100%
Groq—16(9 comp.)
56
33%75%33%
Clarifairelay / router12(6 comp.)
50
33%75%0%
Crusoerelay / router11(11 comp.)
50
27%100%100%
TensorXrelay / router32(32 comp.)
49
34%91%100%
Cloudflare Workers AIrelay / router27(26 comp.)
49
38%93%31%
AI-ROUTERrelay / router5(5 comp.)
48
20%0%100%
Amazon Bedrockhyperscaler165(128 comp.)
47
34%31%60%
Fireworks AIrelay / router33(32 comp.)
47
28%91%100%
Together AIopen-weights host39(35 comp.)
46
23%87%51%
Jalapeno Cloudrelay / router17(17 comp.)
43
12%88%0%
Nebius Token Factoryrelay / router20(19 comp.)
43
16%95%74%
Hugging Facerelay / router77(74 comp.)
42
18%94%12%
Syntheticrelay / router10(10 comp.)
42
30%100%100%
LLMTRrelay / router32(26 comp.)
42
19%44%8%
Bothubrelay / router8(6 comp.)
40
33%75%0%
Requestyrelay / router155(127 comp.)
40
31%38%94%
OVHcloud AI Endpointsrelay / router15(12 comp.)
39
17%100%0%
Volcengine Arkrelay / router16(16 comp.)
38
31%25%100%
Basetenrelay / router23(22 comp.)
37
9%96%64%
Friendlirelay / router7(7 comp.)
37
14%100%86%
IteraComputerelay / router11(9 comp.)
37
22%100%100%
ai&relay / router11(10 comp.)
36
0%91%100%
OCI Generative AIrelay / router9(7 comp.)
36
14%56%29%
Ollama Cloudrelay / router24(17 comp.)
36
12%96%100%
UnoRouterrelay / router23(12 comp.)
36
33%57%0%
DigitalOceanrelay / router97(39 comp.)
34
18%48%74%
Vultrrelay / router10(9 comp.)
34
33%100%0%
EmpirioLabs AIrelay / router62(56 comp.)
34
20%60%100%
Zhipu AIfirst-party lab16(14 comp.)
33
7%88%86%
AKI.IOrelay / router8(7 comp.)
32
14%100%43%
CoreWeaverelay / router27(23 comp.)
32
9%96%100%
Neuralwattrelay / router21(17 comp.)
32
24%100%100%
Z.AIrelay / router17(15 comp.)
31
7%88%87%
MiniMax (minimax.cn)open-weights host7(7 comp.)
31
14%100%86%
MiniMax (minimax.io)first-party lab7(7 comp.)
31
14%100%86%
SiliconFlow (China)relay / router47(44 comp.)
31
14%66%14%
ClinePassrelay / router15(15 comp.)
31
7%80%100%
Alibaba (China)relay / router90(77 comp.)
31
17%47%22%
Chutesrelay / router14(13 comp.)
30
15%93%100%
Ofoxrelay / router144(143 comp.)
29
15%30%96%
Googlefirst-party lab39(26 comp.)
29
15%5%65%
NovitaAIrelay / router107(94 comp.)
29
6%82%38%
Modelisrelay / router9(9 comp.)
29
22%22%0%
Ambientrelay / router10(9 comp.)
29
11%100%100%
302.AIrelay / router117(106 comp.)
28
17%25%3%
SiliconFlowrelay / router49(49 comp.)
27
6%65%20%
Pioneerrelay / router112(94 comp.)
27
15%51%100%
Vercel AI Gateway—391(236 comp.)
27
15%26%80%
NanoGPTrelay / router685(332 comp.)
27
16%52%98%
Arceerelay / router7(7 comp.)
26
0%100%100%
CrossModelrelay / router60(60 comp.)
26
12%33%98%
Meganovarelay / router19(18 comp.)
26
11%79%0%
GMI Cloudrelay / router15(15 comp.)
25
13%60%100%
ZenMuxrelay / router128(107 comp.)
25
12%36%80%
LLM Gatewayrelay / router408(403 comp.)
24
8%49%78%
HPC-AIrelay / router9(9 comp.)
24
0%67%100%
TokenGorelay / router13(13 comp.)
23
0%100%92%
Abacusrelay / router108(104 comp.)
23
6%28%45%
Eden AIrelay / router283(275 comp.)
23
8%51%70%
OpenCode Gorelay / router36(34 comp.)
23
3%53%100%
OpenCode Zenrelay / router107(73 comp.)
22
8%36%99%
Impossiblrelay / router76(76 comp.)
22
5%25%93%
AIHubMix—82(65 comp.)
22
8%38%100%
Databricksrelay / router30(24 comp.)
22
4%13%92%
Deep Infraopen-weights host68(67 comp.)
21
4%85%67%
IO.NETrelay / router17(14 comp.)
21
7%88%100%
Vivgrid—30(29 comp.)
20
3%27%97%
Jiekou.AIrelay / router61(59 comp.)
20
7%30%0%
Aurikorelay / router15(15 comp.)
20
0%40%80%
Neonrelay / router46(45 comp.)
19
7%26%82%
Merge Gateway—187(184 comp.)
19
5%44%72%
routing.runrelay / router15(12 comp.)
19
17%67%0%
Perplexity Agent—22(22 comp.)
19
9%18%95%
Heliconerelay / router90(79 comp.)
18
6%31%57%
OrcaRouterrelay / router117(108 comp.)
18
3%32%81%
FrogBotrelay / router26(25 comp.)
16
0%27%92%
FastRouterrelay / router47(36 comp.)
16
0%30%25%
DInferencerelay / router6(6 comp.)
16
0%100%0%
DevPass (LLM Gateway)relay / router194(190 comp.)
16
4%34%74%
Vertexhyperscaler52(47 comp.)
16
6%21%89%
Azure Cognitive Services—74(67 comp.)
15
3%24%61%
Kilo Gatewayrelay / router386(341 comp.)
15
5%38%61%
Azurehyperscaler89(81 comp.)
15
5%24%63%
NEAR AI Cloudrelay / router37(30 comp.)
14
3%24%87%
OpenRouter—377(343 comp.)
13
2%40%63%
SAP AI Core—49(26 comp.)
13
4%6%85%
Cloudflare AI Gateway—47(46 comp.)
13
4%6%89%
Mistralfirst-party lab35(26 comp.)
12
4%74%8%
Poerelay / router137(72 comp.)
12
7%11%72%
OpenAIfirst-party lab48(41 comp.)
12
2%0%78%
DaoXErelay / router9(9 comp.)
10
0%0%100%
Vancinerelay / router11(8 comp.)
10
0%73%100%
Xpersonarelay / router13(12 comp.)
10
8%0%100%
RunInfrarelay / router7(7 comp.)
9
0%100%100%
FreeModel—10(10 comp.)
8
0%0%100%
Anthropicfirst-party lab14(14 comp.)
8
0%0%100%
Opperrelay / router40(40 comp.)
8
3%13%80%
submodelrelay / router9(9 comp.)
7
0%67%0%
GitHub Copilotrelay / router28(26 comp.)
6
0%7%100%
CrofAIrelay / router24(19 comp.)
5
0%83%100%
Vertex (Anthropic)—14(14 comp.)
2
0%0%100%
Xiaomifirst-party lab6(5 comp.)
1
0%67%100%
QiHangrelay / router9(9 comp.)
0
0%0%0%
xAIfirst-party lab12(6 comp.)
0
0%0%100%
StepFun (China)first-party lab8(5 comp.)
0
0%38%100%
Metafirst-party lab5(5 comp.)
0
0%0%100%
StepFun (Global)relay / router8(5 comp.)
0
0%38%100%
Coherefirst-party lab14(5 comp.)
0
0%100%0%
Price position is the mean percentile of a provider's output $/M within each model it serves, over models with ≥ 2 providers. It is a positioning signal, not a quality judgement — and carries the same quant: unknown caveat as every price view.

Positioning quadrant

Price position against cache-pricing coverage (switch axes for open-weights share or catalog size). Bottom-left is cheap with rich cache pricing; the frontier marks providers no one dominates on both axes.

Positioned on published prices and catalog membership (vendor-claimed). There is deliberately no latency/reliability axis — we don't run probes yet, so we won't plot it.

Data: models.dev (MIT). Prices are vendor-published; verify before purchase. Methodology.