MULTI-MODEL INFERENCE API

Same responses. Your choice of model.

Unified API across Claude, GPT-4, Llama, and Mistral. Switch models in one line of code. Compress with theta symbols for 70% cost reduction.

Model Selector
4 MODELS
M

1M = 1 million input tokens

Claude Opus Highest quality
Monthly Cost
$300
Latency (p95)
280ms
Quality Rating
⭐⭐⭐⭐⭐
4
Models Available
1 API
Switch in One Line
60x
Compression Ratio
Claude + GPT-4 + Llama + Mistral in one API
Switch models with one parameter
Theta compression reduces tokens by 60x
99.5% uptime SLA with multi-region redundancy
Claude + GPT-4 + Llama + Mistral in one API
Switch models with one parameter
Theta compression reduces tokens by 60x
99.5% uptime SLA with multi-region redundancy

Every AI provider is different.
Your code shouldn't depend on one.

Build once. Switch models freely. Claude got too expensive? Use Llama. Need raw speed? Mistral. Theta compression makes any model 60x more efficient. Read Docs

Direct Provider APIs
Vendor lock-in
  • Different API formats per provider
  • Switching = rewrite all code
  • Price increases? Stuck paying it
  • Can't A/B test different models
  • No cost transparency across models
Emergent Language
Provider flexibility
  • Unified API across all models
  • Switch with one parameter change
  • Compare costs side-by-side
  • A/B test models in production
  • Built-in compression = 60x efficiency

Try all 4 models risk-free

Free tier: 30 minutes per 12-hour window. Run Claude, GPT-4, Llama, and Mistral back-to-back. No credit card. No commitment.

Get API Key

One API. Four models. Instant switching.

Write once, choose your model. Unified interface across Claude, GPT-4, Llama, and Mistral. Switch provider in one line. Getting Started

1

Initialize Client

Pick your default model. Switch anytime.

from emergent import Inference

client = Inference(
  api_key="...",
  model="claude-opus"
)
2

Call Any Model

Same prompt, different models. Compare quality and speed.

# Use Claude by default
response = client.chat("Hello")

# Switch to Llama for this call
response = client.chat("Hello",
  model="llama-70b")
3

Automatic Compression

Theta symbols compress tokens by 60x. Works on every model.

client = Inference(
  compression="theta"
)

# 60x smaller tokens
response = client.chat(...)

Blazing Fast. Proven at Scale.

Batch processing unlocks massive throughput. 10,646 messages/sec across 3 regions. 77% bandwidth savings on every request.

3,549 msg/sec
Single Region (50-msg batches)
✓ 100% success rate
✓ <50ms p95 latency
✓ Rust-optimized
10,646 msg/sec
3 Regions (3× 3,549)
✓ Zero-copy batching
✓ Geo-distributed
✓ Scales linearly
77% Bandwidth Saved
Every Request
✓ Theta compression
✓ No codec overhead
✓ Persistent
Pro Tip: Use 50-100 message batches for optimal latency/throughput tradeoff. See batching guide for examples.

Test it yourself. Compete globally.

Join thousands of developers stress testing our infrastructure. Real-time leaderboard. Zero credentials required. See who's pushing the limits.

🏆 Top Performers (24h)
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Rank
Participant
Peak RPS
p95 Lat
Success

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Ready to Test?

Fire unlimited requests. No auth, no rate limit. Pure performance. Join the competition and see your name on the leaderboard.

Median Latency
99th Percentile

Token-based pricing. Your choice of model.

Pass-through pricing from each provider. No markup. Pay what the model costs. Theta compression makes everything cheaper.

Free Tier
$0

30 minutes per 12-hour window. Test all models risk-free.

  • All 4 models included
  • 30 min per 12h window
  • No credit card
  • Full API access
Get Free Key
Enterprise
Custom

Volume discounts, dedicated support, custom routing logic.

  • Volume pricing negotiation
  • Multi-model A/B testing
  • Priority support
  • Custom integrations
Contact Sales