GPT-5.3 Codex Spark OpenAI
💰 Total Cost Calculation (from Plugin)
Output: $0.007000 (rounded ~ $0.01)
Output: $0.007000 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 2,000 output tokens:
- Input Cost: $0.043750 (rounded ~ $0.04)
- Output Cost: $0.007000 (rounded ~ $0.01)
- Total Cost: $0.031063 (rounded ~ $0.03)
- Cost per 1K tokens: $0.000305
- Tokens per dollar: 3,283,702 tokens
- Context Window: 200000 tokens
Speed & Performance Analysis
With a processing speed of 1,000 tokens per second and 100ms time to first token:
- Processing Time: 1 minute, 44.22 seconds
- Latency: 100 milliseconds to first token
- Base Throughput: 1,000 tokens/second
- Effective Throughput: 980 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for GPT-5.3 Codex Spark. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.
Get a $39 personalized AI Architecture Audit. PDF tailored to your stack, delivered in under 60 seconds. 7-day no-questions-asked refund.
Get my instant AI audit — $39 →Claude Sonnet 4.6 Anthropic 1000000
💰 Total Cost Calculation (from Plugin)
Output: $0.007500 (rounded ~ $0.01)
Output: $0.007500 (rounded ~ $0.01)
Unit: $0.000000
Fees: $0.000000
Advanced Cost Breakdown (from Plugin)
Detailed Cost Analysis (from Plugin)
For 100,000 input tokens and 2,000 output tokens:
- Input Cost: $0.075000 (rounded ~ $0.08)
- Output Cost: $0.007500 (rounded ~ $0.01)
- Total Cost: $0.048750 (rounded ~ $0.05)
- Cost per 1K tokens: $0.000478
- Tokens per dollar: 2,092,308 tokens
- Context Window: 1000000 tokens
Speed & Performance Analysis
With a processing speed of 450 tokens per second and 200ms time to first token:
- Processing Time: 3 minutes, 51.38 seconds
- Latency: 200 milliseconds to first token
- Base Throughput: 450 tokens/second
- Effective Throughput: 441 tokens/second (temperature-adjusted)
Best Use Cases
Want this applied to YOUR actual stack?
This calculator shows the math for Claude Sonnet 4.6. Your decision needs more — current infrastructure, compliance requirements, actual workload patterns, volume tiers — that change which model is right for you.
Get a $39 personalized AI Architecture Audit. PDF tailored to your stack, delivered in under 60 seconds. 7-day no-questions-asked refund.
Get my instant AI audit — $39 →✨ Market Recommendations AI Model Registry
← Back to GPT-5.3 Codex Spark| Rank | AI Model & Provider | Total Cost | vs GPT-5.3 Codex Spark | vs Claude Sonnet 4.6 |
|---|---|---|---|---|
| 🏆 |
Mistral Small 3
Mistral AI
|
$0.001525 Best Value | ↓ 95.1% cheaper | ↓ 96.9% cheaper |
| 🥈 |
Gemini 3.1 Flash Lite
Google
|
$0.004188 | ↓ 86.5% cheaper | ↓ 91.4% cheaper |
| 🥉 |
Gemini 3.5 Flash-Lite
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 82.7% cheaper | ↓ 89% cheaper |
| #4 |
Gemini 2.5 Flash
Google
|
$0.005375 (rounded ~ $0.01) | ↓ 82.7% cheaper | ↓ 89% cheaper |
| #5 |
Mistral Large 3
Mistral AI
|
$0.007625 (rounded ~ $0.01) | ↓ 75.5% cheaper | ↓ 84.4% cheaper |
| #6 |
Gemini 3.8 Flash
Google
|
$0.012188 (rounded ~ $0.01) | ↓ 60.8% cheaper | ↓ 75% cheaper |
| #7 |
GPT-5.4 mini
OpenAI
|
$0.012563 (rounded ~ $0.01) | ↓ 59.6% cheaper | ↓ 74.2% cheaper |
| #8 |
o4-mini Deep Research
OpenAI
|
$0.015750 (rounded ~ $0.02) | ↓ 49.3% cheaper | ↓ 67.7% cheaper |
| #9 |
Claude Haiku 4.5
Anthropic
|
$0.016250 (rounded ~ $0.02) | ↓ 47.7% cheaper | ↓ 66.7% cheaper |
| #10 |
Gemini 3.1 Flash
Google
|
$0.016750 (rounded ~ $0.02) | ↓ 46.1% cheaper | ↓ 65.6% cheaper |
| #11 |
GPT-5.6 Luna
OpenAI
|
$0.016750 (rounded ~ $0.02) | ↓ 46.1% cheaper | ↓ 65.6% cheaper |
| #12 |
o4-mini
OpenAI
|
$0.017325 (rounded ~ $0.02) | ↓ 44.2% cheaper | ↓ 64.5% cheaper |
| #13 |
Gemini 3.6 Flash
Google
|
$0.024375 (rounded ~ $0.02) | ↓ 21.5% cheaper | ↓ 50% cheaper |
| #14 |
Gemini 3.5 Flash
Google
|
$0.025125 (rounded ~ $0.03) | ↓ 19.1% cheaper | ↓ 48.5% cheaper |
| #15 |
GPT-5.3 Instant
OpenAI
|
$0.031063 (rounded ~ $0.03) | Same price | ↓ 36.3% cheaper |
| #16 |
Claude Sonnet 5
Anthropic
|
$0.032500 (rounded ~ $0.03) | ↑ 4.6% more | ↓ 33.3% cheaper |
| #17 |
GPT-5.6 Terra
OpenAI
|
$0.041875 (rounded ~ $0.04) | ↑ 34.8% more | ↓ 14.1% cheaper |
| #18 |
Gemini 2.5 Pro
Google
|
$0.044375 (rounded ~ $0.04) | ↑ 42.9% more | ↓ 9% cheaper |
| #19 |
Claude Sonnet 4.6
Anthropic
|
$0.048750 (rounded ~ $0.05) | ↑ 56.9% more | Same price |
| #20 |
Grok 4.3
xAI
|
$0.059000 (rounded ~ $0.06) | ↑ 89.9% more | ↑ 21% more |
| #21 |
Grok 4.20 Beta
xAI
|
$0.059000 (rounded ~ $0.06) | ↑ 89.9% more | ↑ 21% more |
| #22 |
Gemini 3.1 Pro
Google
|
$0.067000 (rounded ~ $0.07) | ↑ 115.7% more | ↑ 37.4% more |
| #23 |
Claude Opus 4.7
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 161.6% more | ↑ 66.7% more |
| #24 |
Claude Opus 5
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 161.6% more | ↑ 66.7% more |
| #25 |
Claude Opus 4.8
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 161.6% more | ↑ 66.7% more |
| #26 |
Claude Opus 4.6
Anthropic
|
$0.081250 (rounded ~ $0.08) | ↑ 161.6% more | ↑ 66.7% more |
| #27 |
GPT-5.4
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 169.6% more | ↑ 71.8% more |
| #28 |
GPT-5.4 Thinking
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 169.6% more | ↑ 71.8% more |
| #29 |
GPT-5.5 Instant
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 169.6% more | ↑ 71.8% more |
| #30 |
GPT-5.6 Sol
OpenAI
|
$0.083750 (rounded ~ $0.08) | ↑ 169.6% more | ↑ 71.8% more |
| #31 |
Claude Fable 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↑ 393% more | ↑ 214.1% more |
| #32 |
Claude Mythos 5.1
Anthropic
|
$0.153125 (rounded ~ $0.15) | ↑ 393% more | ↑ 214.1% more |
| #33 |
o3 Deep Research
OpenAI
|
$0.157500 (rounded ~ $0.16) | ↑ 407% more | ↑ 223.1% more |
| #34 |
Claude Fable 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↑ 423.1% more | ↑ 233.3% more |
| #35 |
Claude Mythos 5
Anthropic
|
$0.162500 (rounded ~ $0.16) | ↑ 423.1% more | ↑ 233.3% more |
| #36 |
GPT-5.5
OpenAI
|
$0.167500 (rounded ~ $0.17) | ↑ 439.2% more | ↑ 243.6% more |
| #37 |
o3 Pro
OpenAI
|
$0.315000 (rounded ~ $0.32) | ↑ 914.1% more | ↑ 546.2% more |
| #38 |
GPT-6 Astra
OpenAI
|
$0.325000 (rounded ~ $0.33) | ↑ 946.3% more | ↑ 566.7% more |
| #39 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 1100% more | ↑ 664.6% more |
| #40 |
GPT-5.2 Pro
OpenAI
|
$0.372750 (rounded ~ $0.37) | ↑ 1100% more | ↑ 664.6% more |
Mistral Small 3 Mistral AI
Gemini 3.1 Flash Lite Google
Gemini 3.5 Flash-Lite Google
Gemini 2.5 Flash Google
Mistral Large 3 Mistral AI
Gemini 3.8 Flash Google
GPT-5.4 mini OpenAI
o4-mini Deep Research OpenAI
Claude Haiku 4.5 Anthropic
Gemini 3.1 Flash Google
GPT-5.6 Luna OpenAI
o4-mini OpenAI
Gemini 3.6 Flash Google
Gemini 3.5 Flash Google
GPT-5.3 Instant OpenAI
Claude Sonnet 5 Anthropic
GPT-5.6 Terra OpenAI
Gemini 2.5 Pro Google
Claude Sonnet 4.6 Anthropic
Grok 4.3 xAI
Grok 4.20 Beta xAI
Gemini 3.1 Pro Google
Claude Opus 4.7 Anthropic
Claude Opus 5 Anthropic
Claude Opus 4.8 Anthropic
Claude Opus 4.6 Anthropic
GPT-5.4 OpenAI
GPT-5.4 Thinking OpenAI
GPT-5.5 Instant OpenAI
GPT-5.6 Sol OpenAI
Claude Fable 5.1 Anthropic
Claude Mythos 5.1 Anthropic
o3 Deep Research OpenAI
Claude Fable 5 Anthropic
Claude Mythos 5 Anthropic
GPT-5.5 OpenAI
o3 Pro OpenAI
GPT-6 Astra OpenAI
GPT-5.2 Pro OpenAI
GPT-5.2 Pro OpenAI
Code review is the critical gatekeeper in modern software engineering, yet it often becomes a bottleneck as development velocity increases. For teams processing 50-200 KB diffs, selecting the right model depends heavily on the primary intent of the review.
GPT-5.3 Codex Spark is designed for high-throughput, terminal-centric execution. It excels when the review process requires rapid, repetitive linting, syntax checking, or enforcing standardized coding patterns. If your workflow relies on fast, autonomous feedback within a CI/CD pipeline, Codex Spark’s architecture prioritizes speed and structural precision, making it an ideal candidate for automating the ‘routine’ portion of your code review checklist.
Conversely, Claude Sonnet 4.6 is built for deep reasoning and complex architectural analysis. When reviewing pull requests that involve significant logic changes, refactoring, or multi-file dependencies, Sonnet 4.6’s ability to maintain context and understand the ‘why’ behind a change is superior. It is better equipped to identify subtle bugs, security vulnerabilities, or architectural deviations that require more nuanced human-like judgment.
For many teams, the most effective strategy is a tiered approach. Use GPT-5.3 Codex Spark for high-volume, routine scans that require near-instant response times, and reserve Claude Sonnet 4.6 for complex, high-stakes reviews where reasoning capability outweighs raw speed. By tailoring your model choice to the specific nature of the diff—routine cleanup versus logic-heavy refactoring—you can optimize for both developer velocity and code quality without compromising on security or maintenance standards.