Inference availability
Providers Provider-specific identifiers, limits, and listed prices per million tokens. Every row links back to the provider's own documentation.
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Specification
Capabilities Recorded from the source catalog and provider listings.
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Reasoning
Unknown
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Tool calling
Unknown
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Structured output
Unknown
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Attachments
Unknown
✓
Vision input
Yes
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Open weights
Unknown
Model family Not documented
Knowledge cutoff Not documented
License Not documented
Release date Not documented
Model ID openai/gpt-4.1:batch
Published evaluations
Benchmarks Every result stays attached to its source, version, metric and harness. Scores from different versions are never merged, and the profile below plots each benchmark against its own population rather than on a shared scale.
Benchmark registry
Benchmark profile
Design Arena: w…Design Arena: website
Design Arena: c…Design Arena: codecategories
Design Arena: d…Design Arena: dataviz
Design Arena: g…Design Arena: gamedev
Design Arena: u…Design Arena: uicomponent
Design Arena: 3dDesign Arena: 3d
This model — Design Arena: website: 1062 elo (17.7th percentile)
This model — Design Arena: codecategories: 1055 elo (15.0th percentile)
This model — Design Arena: dataviz: 1131 elo (26.1th percentile)
This model — Design Arena: gamedev: 1119 elo (25.7th percentile)
This model — Design Arena: uicomponent: 1036 elo (14.4th percentile)
This model — Design Arena: 3d: 904 elo (2.3th percentile)
Each axis is this model's percentile among the 6 benchmarks it has published results for, measured against every other model with a score on that same benchmark. Percentiles are used because benchmarks do not share a scale — a 60 on one is not a 60 on another. Hover any point for the raw score.
Design Arena: website
#121 of 147
773.0
median 1208.0
1379.0
Design Arena: codecategories
#119 of 140
819.0
median 1200.0
1416.0
Design Arena: dataviz
#102 of 138
884.0
median 1199.0
1391.0
Design Arena: gamedev
#101 of 136
812.0
median 1195.5
1394.0
Design Arena: uicomponent
#113 of 132
803.0
median 1203.0
1397.0
Design Arena: 3d
#127 of 130
891.0
median 1194.5
1454.0
Each strip shows every published score for that benchmark, with this model marked. The lighter shape behind the ticks is the density of results, and the dashed line is the median.
Cost against capability
Price and performance Listed input price plotted against Design Arena: website, the benchmark with the widest published coverage that this model appears in.
0
731
1462
$0.1
$1
$10
Amazon: Nova Premier 1.0 — $2.5/M, score 858.0
Amazon: Nova Pro 1.0 — $0.8/M, score 819.0
Claude Fable 5 — $10/M, score 1329.0
Anthropic: Claude Fable 5 (batch) — $5/M, score 1329.0
Anthropic: Claude Haiku 4.5 — $1/M, score 1146.0
Anthropic: Claude Haiku 4.5 (batch) — $0.5/M, score 1146.0
Anthropic: Claude Opus 4 — $15/M, score 1188.0
Anthropic: Claude Opus 4.1 — $15/M, score 1200.0
Anthropic: Claude Opus 4.1 (batch) — $7.5/M, score 1200.0
Anthropic: Claude Opus 4.5 — $5/M, score 1271.0
Anthropic: Claude Opus 4.5 (batch) — $2.5/M, score 1271.0
Anthropic: Claude Opus 4.6 — $5/M, score 1316.0
Anthropic: Claude Opus 4.6 (batch) — $2.5/M, score 1316.0
Anthropic: Claude Opus 4.7 — $5/M, score 1318.0
Anthropic: Claude Opus 4.7 (batch) — $2.5/M, score 1318.0
Anthropic: Claude Opus 4.8 — $5/M, score 1270.0
Anthropic: Claude Opus 4.8 (batch) — $2.5/M, score 1270.0
Claude Opus 5 — $5/M, score 1342.0
Claude Opus 5 (batch) — $2.5/M, score 1342.0
Anthropic: Claude Sonnet 4 — $3/M, score 1169.0
Anthropic: Claude Sonnet 4.5 — $3/M, score 1213.0
Anthropic: Claude Sonnet 4.5 (batch) — $1.5/M, score 1213.0
Anthropic: Claude Sonnet 4.6 — $3/M, score 1309.0
Anthropic: Claude Sonnet 4.6 (batch) — $1.5/M, score 1309.0
Claude Sonnet 5 — $2/M, score 1296.0
Anthropic: Claude Sonnet 5 (batch) — $1/M, score 1296.0
Arcee AI: Trinity Large Thinking — $0.22/M, score 1160.0
DeepSeek Chat — $0.14/M, score 1143.0
DeepSeek: DeepSeek V3.1 — $0.25/M, score 1146.0
DeepSeek: R1 0528 — $0.5/M, score 1172.0
DeepSeek: DeepSeek V3.1 Terminus — $0.27/M, score 1210.0
DeepSeek: DeepSeek V3.2 — $0.269/M, score 1198.0
DeepSeek: DeepSeek V3.2 Exp — $0.27/M, score 1202.0
DeepSeek V4 Flash — $0.14/M, score 1231.0
DeepSeek V4 Flash 0731 — $0.09/M, score 1269.0
DeepSeek V4 Pro — $0.435/M, score 1259.0
Gemini 2.5 Flash — $0.3/M, score 1138.0
Google: Gemini 2.5 Flash (batch) — $0.15/M, score 1138.0
Gemini 2.5 Pro — $1.25/M, score 1191.0
Google: Gemini 2.5 Pro (batch) — $0.625/M, score 1191.0
Gemini 3 Flash Preview — $0.5/M, score 1219.0
Google: Gemini 3 Flash Preview (batch) — $0.25/M, score 1219.0
Gemini 3.1 Flash Lite Preview — $0.25/M, score 1105.0
Gemini 3.1 Pro Preview — $2/M, score 1274.0
Google: Gemini 3.1 Pro Preview (batch) — $1/M, score 1274.0
Gemini 3.5 Flash — $1.5/M, score 1283.0
Google: Gemini 3.5 Flash (batch) — $0.75/M, score 1283.0
Gemini 3.6 Flash — $1.5/M, score 1322.0
Google: Gemini 3.6 Flash (batch) — $0.75/M, score 1322.0
Inception: Mercury 2 — $0.25/M, score 1018.0
Meta: Llama 4 Maverick — $0.2/M, score 894.0
Meta: Llama 4 Scout — $0.1/M, score 773.0
Muse Spark 1.1 — $1.25/M, score 1296.0
MiniMax: MiniMax M2 — $0.255/M, score 1166.0
MiniMax: MiniMax M2.1 — $0.3/M, score 1225.0
MiniMax: MiniMax M2.5 — $0.22/M, score 1245.0
MiniMax: MiniMax M2.7 — $0.27/M, score 1269.0
MiniMax: MiniMax M3 — $0.3/M, score 1285.0
MiniMax: MiniMax M3 (batch) — $0.15/M, score 1285.0
Mistral: Codestral 2508 — $0.3/M, score 1036.0
Mistral: Ministral 3 14B 2512 — $0.2/M, score 1104.0
Mistral: Ministral 3 3B 2512 — $0.1/M, score 1051.0
Mistral: Ministral 3 8B 2512 — $0.15/M, score 1088.0
Mistral: Mistral Large 3 2512 — $0.5/M, score 1185.0
Mistral: Mistral Medium 3 — $0.4/M, score 1102.0
Mistral: Mistral Medium 3.1 — $0.4/M, score 1156.0
Mistral: Mistral Small 3.2 24B — $0.094/M, score 919.0
MoonshotAI: Kimi K2 0711 — $0.57/M, score 1074.0
MoonshotAI: Kimi K2 0905 — $0.6/M, score 1130.0
Kimi K2 Thinking — $0.6/M, score 1136.0
Kimi K2.5 — $0.6/M, score 1273.0
Kimi K2.6 — $0.95/M, score 1298.0
Kimi K2.7 Code — $0.95/M, score 1298.0
MoonshotAI: Kimi K2.7 Code (batch) — $0.475/M, score 1298.0
Kimi K3 — $3/M, score 1379.0
Nex AGI: Nex-N2-Pro — $0.25/M, score 1250.0
Nemotron 3 Ultra 550B A55B — $0.5/M, score 1133.0
NVIDIA: Nemotron 3 Ultra (batch) — $0.3/M, score 1133.0
GPT-4.1 — $2/M, score 1062.0
GPT-4.1 mini — $0.4/M, score 1021.0
OpenAI: GPT-4.1 Mini (batch) — $0.2/M, score 1021.0
GPT-4.1 nano — $0.1/M, score 996.0
OpenAI: GPT-4.1 Nano (batch) — $0.05/M, score 996.0
OpenAI: GPT-4.1 (batch) — $1/M, score 1062.0
GPT-4o — $2.5/M, score 854.0
OpenAI: GPT-4o (batch) — $1.25/M, score 854.0
GPT-5 — $1.25/M, score 1208.0
GPT-5 Mini — $0.25/M, score 1148.0
OpenAI: GPT-5 Mini (batch) — $0.125/M, score 1148.0
GPT-5 Nano — $0.05/M, score 1125.0
OpenAI: GPT-5 Nano (batch) — $0.025/M, score 1125.0
GPT-5.1 — $1.25/M, score 1211.0
GPT-5.1 Codex — $1.07/M, score 1184.0
GPT-5.1 Codex mini — $0.22/M, score 1134.0
OpenAI: GPT-5.1 (batch) — $0.625/M, score 1211.0
GPT-5.2 — $1.75/M, score 1217.0
OpenAI: GPT-5.2 (batch) — $0.875/M, score 1217.0
GPT-5.3 Codex — $1.75/M, score 1186.0
GPT-5.4 — $2.5/M, score 1243.0
OpenAI: GPT-5.4 (batch) — $1.25/M, score 1243.0
GPT-5.5 — $5/M, score 1280.0
OpenAI: GPT-5.5 (batch) — $2.5/M, score 1280.0
OpenAI: GPT-5 (batch) — $0.625/M, score 1208.0
GPT OSS 120B — $0.03/M, score 991.0
GPT OSS 20B — $0.03/M, score 876.0
o3 — $2/M, score 1059.0
OpenAI: o3 (batch) — $1/M, score 1059.0
o4-mini — $1.1/M, score 1008.0
OpenAI: o4 Mini (batch) — $0.55/M, score 1008.0
Qwen: Qwen3 235B A22B — $0.455/M, score 1054.0
Qwen: Qwen3 235B A22B Instruct 2507 — $0.09/M, score 1081.0
Qwen: Qwen3 235B A22B Thinking 2507 — $0.23/M, score 1076.0
Qwen: Qwen3 30B A3B — $0.12/M, score 978.0
Qwen: Qwen3 30B A3B Thinking 2507 — $0.2/M, score 954.0
Qwen: Qwen3 Coder 480B A35B — $0.3/M, score 1182.0
Qwen: Qwen3 Coder 30B A3B Instruct — $0.07/M, score 1111.0
Qwen: Qwen3 Max — $0.78/M, score 1142.0
Qwen: Qwen3.5 397B A17B — $0.39/M, score 1214.0
Qwen: Qwen3.5 Plus 2026-02-15 — $0.26/M, score 1211.0
Qwen: Qwen3.6 Plus — $0.325/M, score 1262.0
Qwen: Qwen3.7 Max — $1.475/M, score 1297.0
Qwen: Qwen3.7 Plus — $0.32/M, score 1295.0
Step 3.7 Flash — $0.185/M, score 1211.0
Hy3 — $0.066/M, score 1206.0
Inkling — $1.87/M, score 1233.0
Thinking Machines: Inkling (batch) — $0.5/M, score 1233.0
SpaceXAI: Grok 4.20 — $1.25/M, score 1251.0
SpaceXAI: Grok 4.3 — $1.25/M, score 1215.0
SpaceXAI: Grok 4.5 — $2/M, score 1320.0
MiMo-V2.5 — $0.14/M, score 1293.0
MiMo-V2.5-Pro — $0.435/M, score 1300.0
Z.ai: GLM 4.5 — $0.6/M, score 1193.0
Z.ai: GLM 4.5 Air — $0.13/M, score 1170.0
Z.ai: GLM 4.6 — $0.5/M, score 1198.0
Z.ai: GLM 4.7 — $0.4/M, score 1249.0
Z.ai: GLM 4.7 Flash — $0.06/M, score 1217.0
Z.ai: GLM 5 — $0.95/M, score 1272.0
Z.ai: GLM 5 Turbo — $1.2/M, score 1294.0
Z.ai: GLM 5.1 — $0.952/M, score 1295.0
Z.ai: GLM 5.2 — $0.56/M, score 1338.0
Z.ai: GLM 5.2 (batch) — $0.7/M, score 1338.0
Z.ai: GLM 5V Turbo — $1.2/M, score 1253.0
OpenAI: GPT-4.1 (batch)
Input price per million tokens (log scale)
Elo
The stepped line is the efficient frontier: at each price, the best score available for that money or less. A model sitting on it is not being beaten by anything cheaper. Price is log-scaled because listed rates span four orders of magnitude. Only models with both a listed price and a score on this benchmark can appear.
Catalog activity
Change log Field-level changes detected between successful source imports.
Full change log No changes recorded This record has not changed within the retained import history.
Provenance
Sources & verification Every figure on this page traces back to one of these records.
Methodology
Last verified Aug 06, 2026
Status Source-linked
Confidence Medium
Catalog source OpenRouter
Public API
Use this record Fetch the complete source-linked model record. No key, no account, no rate-limited tier.
API documentation
Endpoint Copy
GET https://www.modelbench.lol/api/v1/models/openai/gpt-4.1:batchcurl Copy
curl "https://www.modelbench.lol/api/v1/models/openai/gpt-4.1:batch"
Common questions
Frequently asked questions Answered directly from the stored record — nothing here is generated beyond the catalog's own fields.
What is OpenAI: GPT-4.1 (batch)?
GPT-4.1 is a flagship large language model optimized for advanced instruction following, real-world software engineering, and long-context reasoning. It supports a 1 million token context window and outperforms GPT-4o and. It is published by OpenAI and catalogued here from OpenRouter.
What is the context length of OpenAI: GPT-4.1 (batch)?
OpenAI: GPT-4.1 (batch) accepts up to 1.04758M tokens of context and returns up to 32.768K output tokens.
Does OpenAI: GPT-4.1 (batch) support tool calling and structured output?
Provider catalogs list support for image input.
