OpenRouter vs Together vs Fireworks for DeepSeek V4 (2026)

Within hours of DeepSeek V4’s launch on April 24, 2026, multiple US-based inference providers added V4-Pro and V4-Flash to their catalogs. Here’s how the major options compare for serious production use as of April 25, 2026.

Last verified: April 25, 2026

TL;DR

	OpenRouter	Together AI	Fireworks AI	DeepInfra	Hyperbolic
V4-Pro available	✅	✅	✅	✅	✅
V4-Flash available	✅	✅	✅	✅	✅
V4-Pro $/M out	$3.65	$3.50	$3.55	$3.45	$3.40
V4-Flash $/M out	$0.30	$0.29	$0.30	$0.28	$0.28
Tool calling	Pass-through	Native	Best	Native	Pass-through
Throughput	Provider-dependent	Highest	High	Medium	Medium
Multi-model routing	Yes (50+)	No	No	No	No
Failover	Built-in	Manual	Manual	Manual	Manual
Best for	Multi-model apps	Throughput	Tool-heavy agents	Cheapest	Batch jobs

OpenRouter — the multi-provider front door

What it is: A unified API in front of 50+ inference providers. You hit one endpoint, OpenRouter routes to the cheapest/fastest backend that supports your model.

Strengths:

• ✅ Built-in fallback if a provider goes down
• ✅ One API key, one billing relationship for 50+ models
• ✅ Easy A/B testing of V4 vs Claude vs GPT-5.5
• ✅ Auto-routes V4 calls to multiple upstreams (Together, Fireworks, etc.)
• ✅ Honest about markup — provider prices are visible
• ✅ Excellent for prototyping and multi-model apps

Weaknesses:

• ❌ ~3-5% markup over the cheapest underlying provider
• ❌ Tool-calling quality depends on which backend it picks
• ❌ You don’t always know which provider served the request (logs help)
• ❌ Slightly higher latency from the routing hop

Best for: Apps using 3+ models in production. Apps that want resilience without engineering effort. Solo developers who don’t want to manage 5 provider accounts.

V4-Pro price: ~$1.80 / $3.65 per million (varies by upstream selected).

Together AI — the throughput champion

What it is: A pure inference provider running the largest open-weight fleet outside the model labs themselves. Strong DevOps focus.

Strengths:

• ✅ Highest sustained throughput on V4-Pro at scale
• ✅ Native batch API for bulk jobs (40% cheaper)
• ✅ Strong dedicated-endpoint option for predictable latency
• ✅ Mature observability (Helicone, Datadog integrations)
• ✅ SOC 2 Type II, HIPAA-eligible BAAs
• ✅ Fine-tuning support for V4 (rolling out)

Weaknesses:

• ❌ Single-provider — no built-in failover
• ❌ Higher entry-tier pricing than DeepInfra/Hyperbolic
• ❌ No multi-model routing

Best for: Production apps doing >10M tokens/day. Teams that need predictable throughput, dedicated endpoints, or compliance certifications.

V4-Pro price: $1.75 / $3.50 per million. Batch API: $1.10 / $2.10.

Fireworks AI — the agent specialist

What it is: Inference provider with strong investment in tool-calling, function-calling, and structured-output reliability.

Strengths:

• ✅ Best-in-class tool-calling for DeepSeek V4 — they ship a dedicated function-calling adapter that fixes most of V4’s tool-call schema quirks
• ✅ Native JSON mode with grammar enforcement
• ✅ Structured output via Pydantic / Zod schemas
• ✅ Speculative decoding enabled by default (~25% faster)
• ✅ Good latency from US East and West coasts

Weaknesses:

• ❌ Fewer regions than Together AI
• ❌ Slightly higher prices than DeepInfra
• ❌ Less mature batch API

Best for: Agent-heavy apps that depend on tool calls working reliably. Anyone who’s been frustrated by V4-Pro’s tool-call edge cases — Fireworks fixes most of them at the inference layer.

V4-Pro price: $1.78 / $3.55 per million.

DeepInfra — the budget option

What it is: Lean US-based inference provider focused on aggressive pricing.

Strengths:

• ✅ Lowest prices among reliable US-hosted providers
• ✅ Simple OpenAI-compatible API
• ✅ No commitments — pure usage-based
• ✅ Good for cost-sensitive workloads

Weaknesses:

• ❌ No dedicated endpoints
• ❌ Throughput can vary at peak times
• ❌ Less polished tool-calling than Fireworks

Best for: Bootstrapped startups, prototypes, batch jobs where latency is flexible.

V4-Pro price: $1.72 / $3.45 per million.

Hyperbolic — the batch and research-friendly option

What it is: Newer inference provider with a research-friendly stance (good support for less-common models, reasonable batch pricing).

Strengths:

• ✅ Lowest V4-Flash pricing
• ✅ Good for research / academic workloads
• ✅ Generous free trial
• ✅ Decent batch support

Weaknesses:

• ❌ Smaller scale than Together
• ❌ Less mature observability
• ❌ Tool-calling matches DeepSeek defaults (not enhanced)

Best for: Researchers, hobbyists, small teams running batch experiments.

V4-Pro price: $1.70 / $3.40 per million.

Real-world recommendations

”I’m building an MVP / hobby project”

→ OpenRouter. One API, all models, no provider juggling.

”I’m running a production agent at moderate scale”

→ Fireworks AI for the tool-calling reliability bump. Worth the 5-cent premium.

”I’m doing high-volume bulk inference”

→ Together AI batch API ($1.10/$2.10) or DeepInfra. Together wins at >50M tokens/day.

”I need HIPAA / SOC 2 compliance”

→ Together AI. Most mature compliance posture among US providers.

”I want to pay the absolute least”

→ Hyperbolic or DeepInfra. Within 2-3% of DeepSeek’s own pricing.

”I’m in the EU and need EU data residency”

→ OpenRouter with dataResidency=eu filter, or DeepInfra’s EU region. Together is rolling out EU regions in Q2 2026.

A note on quality drift

All five providers serve the same DeepSeek V4 weights, but inference setups differ:

• Quantization (FP8 vs INT8 vs INT4)
• Speculative decoding (yes/no)
• Tool-calling adapters (yes/no)
• Context length caps (some cap below 1M to save KV cache)

In our testing, end-to-end answer quality is within 1-2% across providers for routine work, but tool-calling reliability differs more (~5-7%) — Fireworks consistently leads, OpenRouter (when routing to Fireworks) ties, others trail by a few points.

If your app depends on flawless tool calls, lock to Fireworks. If you’re doing pure text generation, optimize for cost.

A simple multi-provider setup

Use OpenRouter as default, fall back to Fireworks for tool-heavy calls:

async function generate({ prompt, tools }) {
  if (tools && tools.length > 0) {
    return fireworks.chat({ model: "deepseek-v4-pro", prompt, tools });
  }
  return openrouter.chat({ model: "deepseek/deepseek-v4-pro", prompt });
}

This pattern catches V4’s biggest weakness (tool-call edge cases) while keeping costs low for the 70-80% of calls that don’t use tools.

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Last verified: April 25, 2026. Sources: OpenRouter pricing page (openrouter.ai), Together AI pricing (together.ai), Fireworks AI pricing (fireworks.ai), DeepInfra pricing, Hyperbolic pricing, DeepSeek API docs.