OpenAI · o-series · Reasoning
o4-mini pricing and limits
A smaller, faster OpenAI reasoning model at roughly half the o3 rate. Popular for coding and math agents where reasoning helps but o3 cost is hard to justify.
| Line | Tokens | Rate / 1M | Cost |
|---|---|---|---|
| Input, uncached | 6,000 | $1.10 | $0.00660 |
| Input, cache read | 14,000 | $0.28 | $0.00385 |
| Output | 4,000 | $4.40 | $0.0176 |
- Input / 1M
- $1.10
- Output / 1M
- $4.40
- Cached / 1M
- $0.28
- Cache write / 1M
- n/a
- Blended 3:1
- $1.93
- Context
- 200K
What drives o4-mini cost
Reasoning tokens are billed as output, exactly as on o3. The lower rate makes it tempting to run at high effort everywhere, and a high effort setting on simple prompts mostly buys tokens, not accuracy.
Cached input is a quarter of the input price. Coding agents that resend a large repository map with each step see meaningful savings when that map is kept stable at the top of the prompt.
Cost of a typical call
Take a coding agent step with 20,000 input tokens, 14,000 of them served from cache, and 4,000 output tokens. At o4-mini list prices ($1.10 input, $0.28 cached input, $4.40 output per 1M) one call costs $0.0280, against $0.0396 with no cache hits. At 100,000 calls a month that is $2,805, or $3,960 uncached.
Blended at a 3:1 input to output ratio, o4-mini costs $1.93 per 1M tokens. Routing the same call to the fallback in the policy below, GPT-5 mini, costs $0.00985, which is what a tenant pays you in COGS once they cross the hard cap and PALM SOUQ downgrades instead of blocking.
Cost comparison
o4-mini against three alternatives
The same coding agent step priced on o3, GPT-5 mini, Claude Haiku 4.5. Move the sliders to match your traffic; models without a cache-read rate bill every input token in full.
Benchmark quality per task before switching. A cheaper model that needs more steps or longer outputs can cost more per finished task than its rate suggests, which is why PALM SOUQ reports cost per feature, not only per token.
o4-mini this guide
$0.0280 per call
$2,805 / mo
baseline
o3
$0.0510 per call
$5,100 / mo
+82% vs o4-mini
GPT-5 mini
$0.00985 per call
$985 / mo
-65% vs o4-mini
Claude Haiku 4.5
$0.0274 per call
$2,740 / mo
-2% vs o4-mini
List prices from the PALM SOUQ LLM Price Index, computed per call as uncached input + cache reads + output. Reasoning tokens count as output on reasoning models.
Rate limits by usage tier
Per-organization TPM and RPM by usage tier. Reasoning models often have different ceilings from non-reasoning models at the same tier, so check the limits page for your organization before load testing.
Exact limits vary by account tier and change over time, so we do not reprint them here. Check the limits page for your own account in the OpenAI documentation at platform.openai.com/docs. PALM SOUQ enforces your own per-tenant limits in front of the provider's, so a single customer cannot consume the shared allowance that every other tenant depends on.
Circuit-breaker best practices
Combine a reasoning token ceiling with tool thrashing detection. Coding agents on o4-mini can alternate between two failing fixes indefinitely, and the oscillating argument check catches the A, B, A, B pattern within a few steps.
Use a per-feature budget for code generation so that one heavy automation feature cannot consume the budget of interactive users.
When a breaker trips, the gateway answers in under 50 ms with HTTP 429 and X-PalmSouq-Reason: circuit_breaker_triggered, before the request reaches OpenAI. Your agent framework sees a normal rate-limit response and stops, and the audit log records which heuristic fired and for which tenant.
# palmsouq.policy.yaml
policy: o4-mini-pro
match:
model: o4-mini
tier: pro # from X-PalmSouq-Tier
budgets:
monthly_usd: 250 # per tenant
soft_cap_pct: 80 # webhook to your app
on_hard_cap: fallback # or: block (HTTP 429)
fallback:
- gpt-5-mini
breakers:
tool_thrashing: { identical_calls: 3, window_steps: 8 }
token_velocity: { max_tokens_per_s: 50000, window_s: 10 }
semantic_echo: { repeats: 3 }
max_steps: 20
max_reasoning_tokens: 10000 # per request
cache:
meter_reads: true- budgetsPer-tenant monthly dollar cap with an 80% soft-cap webhook, keyed by X-PalmSouq-Tenant.
- fallbackAt the hard cap, requests reroute to GPT-5 mini ($0.69 blended per 1M) instead of failing.
- breakersAll four loop heuristics on, evaluated in the request path with under 5 ms added latency.
Where it fits
Coding assistants, test generation, math and data analysis where step-by-step reasoning improves results and volume makes o3 too expensive.
Provider documentation: platform.openai.com/docs
o4-mini pricing questions
How much does o4-mini cost per million tokens?
At list price o4-mini costs $1.10 per 1M input tokens and $4.40 per 1M output tokens, with cached input at $0.28 per 1M. Prices were last reviewed in the PALM SOUQ LLM Price Index and are for the standard tier and shortest context band.
Does o4-mini support prompt caching?
Yes. Cached input is billed at $0.28 per 1M tokens against $1.10 for uncached input. PALM SOUQ records cached tokens per tenant from the provider's usage data, so cache savings show up in each customer's COGS.
What are the o4-mini rate limits?
Per-organization TPM and RPM by usage tier. Reasoning models often have different ceilings from non-reasoning models at the same tier, so check the limits page for your organization before load testing. For your account's exact numbers, see the OpenAI documentation at platform.openai.com/docs.
How do I stop runaway o4-mini agent loops?
Combine a reasoning token ceiling with tool thrashing detection. Coding agents on o4-mini can alternate between two failing fixes indefinitely, and the oscillating argument check catches the A, B, A, B pattern within a few steps. The sample policy on this page enables all four PALM SOUQ heuristics with a max step cap of 20 and falls back to GPT-5 mini at the hard cap.
Is there a batch discount for o4-mini?
50% off input and output through the Batch API (24-hour completion window). Batch traffic suits evaluations, backfills and nightly enrichment jobs that do not need a real-time answer.
Govern o4-mini spend per customer.
Point your OpenAI client at gateway.palmsouqltd.com, pass X-PalmSouq-Tenant, and every o4-mini token is attributed, capped and protected by circuit breakers.
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