GPT-4 Turbo (batch) Paid vs RERelace Apply 3 Paid
GPT-4 Turbo (batch) vs Relace Apply 3 compared — price per token, context window, multimodality, openness and which to choose. Full 2026 breakdown.
GPT-4 Turbo (batch) — full profile › · Relace Apply 3 — full profile ›
Prices & specs refreshed from live data · olud.ai
Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.
$15 /M outputManaged API (no infra to run)
$1.25 /M outputManaged API (no infra to run)
GPT-4 Turbo (batch) vs Relace Apply 3 specs
| Spec | GPT-4 Turbo (batch) | Relace Apply 3 | Winner |
|---|---|---|---|
| Maker | OpenAI | Relace | – |
| Type | Proprietary | Proprietary | – |
| Context window | 128K tokens | 256K tokens | RERelace Apply 3 |
| Input price | $5/M | $0.85/M | RERelace Apply 3 |
| Output price | $15/M | $1.25/M | RERelace Apply 3 |
| Vision / multimodal | Yes | No | |
| Tool / function calling | Yes | No | |
| Self-hostable | No (API only) | No (API only) | – |
| License | Proprietary | Proprietary | – |
Price gap & when to choose each
Relace Apply 3 is ~12× cheaper than GPT-4 Turbo (batch) on output tokens ($1.25 vs $15 per M tokens).
- You want frontier performance through a managed API
- You value reliability & ecosystem
- You don't want to manage infrastructure
- You want frontier performance through a managed API
- You need the longer 256K context window
- You want the lower output price
- You value reliability & ecosystem
- You don't want to manage infrastructure
Feature comparison
| Capability | GPT-4 Turbo (batch) | Relace Apply 3 |
|---|---|---|
| Open weights (downloadable) | ✗ | ✗ |
| Self-hostable | ✗ | ✗ |
| Runs fully offline | ✗ | ✗ |
| Vision / multimodal | ✓ | ✗ |
| Tool / function calling | ✓ | ✗ |
| 1M+ context window | ✗ | ✗ |
Benchmarks: GPT-4 Turbo (batch) vs Relace Apply 3
Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).
Benchmark data by Artificial Analysis.
How GPT-4 Turbo (batch) and Relace Apply 3 score
| Criterion | GPT-4 Turbo (batch) | Relace Apply 3 |
|---|---|---|
| Cost-efficiency | 3.0 | 4.5 |
| Context window | 3.5 | 4.0 |
| Openness | 1.5 | 1.5 |
| Self-hosting | 1.0 | 1.0 |
| Multimodality | 5.0 | 2.0 |
Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.
What each model is
GPT-4 Turbo (batch) Paid
The latest GPT-4 Turbo model with vision capabilities. Vision requests can now use JSON mode and function calling. Training data: up to December 2023.
Relace Apply 3 Paid
Relace Apply 3 is a specialized code-patching LLM that merges AI-suggested edits straight into your source files. It can apply updates from GPT-4o, Claude, and others into your files at...
Frequently asked questions
GPT-4 Turbo (batch) vs Relace Apply 3 — which is cheaper?
Relace Apply 3 is cheaper on output ($1.25/M vs $15/M).
Which has the larger context window?
Relace Apply 3 offers the larger context window (256K tokens).
GPT-4 Turbo (batch) vs Relace Apply 3 — which should I pick in 2026?
Choose Relace Apply 3 for the lower output price ($1.25/M vs $15/M). It also gives you the larger 256K context window.
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