Cheaper alternatives to GPT-4.1

OpenAI LMArena 1382.3 $3.50/M on a balanced workload prices as of 2026-08-28

9 models are both better and cheaper, giving up nothing.

Of the 133 models carrying both an independent score and a published price at the same delivery mode, 63 score at least as high as GPT-4.1 and cost no more under at least one workload. 62 of them are genuinely cheaper; the rest match the price and win on score alone. 9 match or beat it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. 54 do not, and every row names what it drops.

Dominance is not a property of a model. It is a property of a model, a capability lens and a workload, and all three are named on every row. Scores are LMArena Elo, used under CC BY 4.0 from the official dataset; prices are blended per million tokens. A higher score is not a drop-in replacement.

This page is built from that comparison and nothing else. When no model is both better and cheaper than GPT-4.1, it is not generated.

Where it holds

WorkloadGPT-4.1 $/MBetter and cheaperWith a trade
Balanced$3.50954
Summarise$1.87954
Chat$3.95752
Code gen$5.48752
Agentic$2.01953

Workload mixes are defined on the methodology page. Cached input is priced at the cached rate, and reasoning tokens at the worse of the reasoning and output rates.

What you would be replacing

Intelligence1382.3
Context window1.0M
Max output33K
Input modesimage, text, file
Tool useyes
Extended reasoningno

A replacement has to clear every line above, not just the score. Full record for GPT-4.1.

Better and cheaper, nothing given up 9

Each of these matches or beats GPT-4.1 on context, maximum output, input modes, tool use and reasoning, scores at least as high, and costs no more.

#ModelIntelligence$/MHolds under
1Gemini 3.7 Flash Google1490.2 +107.9$0.750
  • Balanced −79%
  • Summarise −81%
  • Chat −78%
  • Code gen −77%
  • Agentic −80%
2Gemini 3.5 Flash Google1482.6 +100.3$3.38
  • Balanced −4%
  • Summarise −20%
  • Agentic −9%
3Muse Spark 1.1 Meta1478.3 +96$2.00
  • Balanced −43%
  • Summarise −42%
  • Chat −46%
  • Code gen −46%
  • Agentic −48%
4Gemini 3.6 Flash Google1476.5 +94.2$1.50
  • Balanced −57%
  • Summarise −62%
  • Chat −56%
  • Code gen −54%
  • Agentic −60%
5Gemini 2.5 Pro Google1457.3 +75$3.44
  • Balanced −2%
  • Summarise −27%
  • Agentic −6%
6Gemini 3.5 Flash Lite Google1436.5 +54.2$0.850
  • Balanced −76%
  • Summarise −82%
  • Chat −72%
  • Code gen −71%
  • Agentic −77%
7GPT-5.6 Luna OpenAI1428.5 +46.2$0.450
  • Balanced −87%
  • Summarise −89%
  • Chat −86%
  • Code gen −86%
  • Agentic −88%
8Gemini 2.5 Flash Google1417.3 +35$0.850
  • Balanced −76%
  • Summarise −82%
  • Chat −72%
  • Code gen −71%
  • Agentic −77%
9Gemini 3.1 Flash Lite Preview Google1414.8 +32.5$0.563
  • Balanced −84%
  • Summarise −87%
  • Chat −83%
  • Code gen −82%
  • Agentic −85%

Cheaper and higher-scoring, but you give something up 54

These score at least as high and cost no more on the two plotted axes, and lose something that is not on them. Read the last column before switching.

ModelIntelligence$/MHolds underWhat you give up
Qwen3.8 Max Qwen1481.9 +99.6$3.00
  • Balanced −14%
  • Summarise −9%
  • Chat −22%
  • Code gen −22%
  • Agentic −22%
  • 1.0M → 1.0M context
  • no file input
GLM 5.3 Z.ai1476.9 +94.6$2.15
  • Balanced −39%
  • Summarise −35%
  • Chat −43%
  • Code gen −43%
  • Agentic −42%
  • no image, file input
MiMo-V2.5-Pro Xiaomi1465 +82.7$0.544
  • Balanced −84%
  • Summarise −82%
  • Chat −88%
  • Code gen −88%
  • Agentic −88%
  • no image, file input
GLM 5.2 Z.ai1465.4 +83.1$1.83
  • Balanced −48%
  • Summarise −44%
  • Chat −51%
  • Code gen −52%
  • Agentic −50%
  • no image, file input
GLM 5.1 Z.ai1464.1 +81.8$1.94
  • Balanced −45%
  • Summarise −41%
  • Chat −49%
  • Code gen −49%
  • Agentic −47%
  • 1.0M → 205K context
  • no image, file input
Qwen3.7 Plus Qwen1456.2 +73.9$0.560
  • Balanced −84%
  • Summarise −84%
  • Chat −84%
  • Code gen −84%
  • Agentic −84%
  • 1.0M → 1.0M context
  • no file input
Kimi K2.6 Moonshot AI1455 +72.7$1.71
  • Balanced −51%
  • Summarise −53%
  • Chat −51%
  • Code gen −50%
  • Agentic −53%
  • 1.0M → 262K context
  • no file input
Grok 4.5 xAI1452.3 +70$3.00
  • Balanced −14%
  • Summarise −8%
  • Chat −22%
  • Code gen −22%
  • Agentic −21%
  • 1.0M → 500K context
Kimi K2.5 Moonshot AI1445.2 +62.9$0.900
  • Balanced −74%
  • Summarise −77%
  • Chat −73%
  • Code gen −73%
  • Agentic −75%
  • 1.0M → 262K context
  • no file input
GLM 5 Z.ai1445.2 +62.9$0.930
  • Balanced −73%
  • Summarise −72%
  • Chat −75%
  • Code gen −75%
  • Agentic −74%
  • 1.0M → 205K context
  • no image, file input
Gemma 4 31B Google1441.7 +59.4$0.152
  • Balanced −96%
  • Summarise −95%
  • Chat −95%
  • Code gen −96%
  • Agentic −95%
  • 1.0M → 262K context
  • 33K → 16K max output
  • no file input
Hy3 Tencent1441.2 +58.9$0.144
  • Balanced −96%
  • Summarise −96%
  • Chat −96%
  • Code gen −96%
  • Agentic −96%
  • 1.0M → 262K context
  • no image, file input
Qwen3.6 Max Preview Qwen1446.3 +64$2.31
  • Balanced −34%
  • Summarise −31%
  • Chat −22%
  • Code gen −25%
  • Agentic −10%
  • 1.0M → 262K context
  • no image, file input
Qwen3.8 27B Qwen1440.8 +58.5$0.956
  • Balanced −73%
  • Summarise −77%
  • Chat −70%
  • Code gen −69%
  • Agentic −73%
  • 1.0M → 1.0M context
  • no file input
GLM 4.6 Z.ai1439.8 +57.5$0.875
  • Balanced −75%
  • Summarise −75%
  • Chat −75%
  • Code gen −75%
  • Agentic −76%
  • 1.0M → 205K context
  • no image, file input
DeepSeek V4 Pro 0423 DeepSeek1439.2 +56.9$1.09
  • Balanced −69%
  • Summarise −63%
  • Chat −75%
  • Code gen −76%
  • Agentic −74%
  • no image, file input
Qwen3.5 397B A17B Qwen1438.3 +56$0.877
  • Balanced −75%
  • Summarise −74%
  • Chat −70%
  • Code gen −72%
  • Agentic −66%
  • 1.0M → 262K context
  • no file input
Grok 4.6 xAI1443.7 +61.4$3.00
  • Balanced −14%
  • Summarise −5%
  • Chat −20%
  • Code gen −22%
  • Agentic −15%
  • 1.0M → 500K context
Qwen3.6 Plus Qwen1436.8 +54.5$0.731
  • Balanced −79%
  • Summarise −78%
  • Chat −75%
  • Code gen −76%
  • Agentic −72%
  • 1.0M → 1.0M context
  • no file input
Inkling Thinking Machines1439.2 +56.9$1.73
  • Balanced −51%
  • Summarise −53%
  • Chat −51%
  • Code gen −50%
  • Agentic −53%
  • no file input
Gemma 4 26B A4B Google1434.6 +52.3$0.138
  • Balanced −96%
  • Summarise −96%
  • Chat −95%
  • Code gen −96%
  • Agentic −94%
  • 1.0M → 262K context
  • 33K → 16K max output
  • no file input
MiniMax M3 MiniMax1434.8 +52.5$0.525
  • Balanced −85%
  • Summarise −85%
  • Chat −85%
  • Code gen −85%
  • Agentic −85%
  • no file input
GLM 4.7 Z.ai1435.3 +53$0.738
  • Balanced −79%
  • Summarise −80%
  • Chat −79%
  • Code gen −78%
  • Agentic −79%
  • 1.0M → 205K context
  • no image, file input
GPT-5.1 OpenAI1441.4 +59.1$3.44
  • Balanced −2%
  • Summarise −27%
  • Agentic −6%
  • 1.0M → 400K context
GLM 5V Turbo Z.ai1436.8 +54.5$1.90
  • Balanced −46%
  • Summarise −43%
  • Chat −49%
  • Code gen −49%
  • Agentic −48%
  • 1.0M → 203K context
  • no file input
DeepSeek V4 Flash 0423 DeepSeek1431.6 +49.3$0.101
  • Balanced −97%
  • Summarise −96%
  • Chat −98%
  • Code gen −98%
  • Agentic −97%
  • no image, file input
MiMo-V2.5 Xiaomi1427.3 +45$0.175
  • Balanced −95%
  • Summarise −94%
  • Chat −96%
  • Code gen −96%
  • Agentic −96%
  • no file input
GLM 4.5 Z.ai1429.4 +47.1$1.00
  • Balanced −71%
  • Summarise −71%
  • Chat −72%
  • Code gen −72%
  • Agentic −73%
  • 1.0M → 131K context
  • no image, file input
R1 0528 DeepSeek1427.9 +45.6$0.912
  • Balanced −74%
  • Summarise −71%
  • Chat −72%
  • Code gen −73%
  • Agentic −67%
  • 1.0M → 164K context
  • no image, file input
DeepSeek V3.2 DeepSeek1424.6 +42.3$0.290
  • Balanced −92%
  • Summarise −88%
  • Chat −93%
  • Code gen −94%
  • Agentic −90%
  • 1.0M → 164K context
  • no image, file input
DeepSeek V3.2 Exp DeepSeek1424.4 +42.1$0.305
  • Balanced −91%
  • Summarise −85%
  • Chat −92%
  • Code gen −94%
  • Agentic −86%
  • 1.0M → 164K context
  • no image, file input
Qwen3 VL 235B A22B Instruct Qwen1420.9 +38.6$0.632
  • Balanced −82%
  • Summarise −86%
  • Chat −78%
  • Code gen −78%
  • Agentic −80%
  • 1.0M → 262K context
  • no file input
Qwen3 235B A22B Instruct 2507 Qwen1419.3 +37$0.205
  • Balanced −94%
  • Summarise −94%
  • Chat −93%
  • Code gen −93%
  • Agentic −92%
  • 1.0M → 262K context
  • 33K → 16K max output
  • no image, file input
DeepSeek V3.1 Terminus DeepSeek1419.6 +37.3$0.453
  • Balanced −87%
  • Summarise −86%
  • Chat −87%
  • Code gen −87%
  • Agentic −85%
  • 1.0M → 164K context
  • no image, file input
Qwen3 Next 80B A3B Instruct Qwen1418.6 +36.3$0.350
  • Balanced −90%
  • Summarise −92%
  • Chat −88%
  • Code gen −87%
  • Agentic −88%
  • 1.0M → 262K context
  • no image, file input
DeepSeek V3.1 DeepSeek1419.1 +36.8$0.825
  • Balanced −76%
  • Summarise −68%
  • Chat −75%
  • Code gen −78%
  • Agentic −64%
  • 1.0M → 164K context
  • no image, file input
Qwen3.5-122B-A10B Qwen1417.9 +35.6$0.715
  • Balanced −80%
  • Summarise −81%
  • Chat −75%
  • Code gen −75%
  • Agentic −73%
  • 1.0M → 262K context
  • no file input
Mistral Medium 3.5 Mistral1420.9 +38.6$3.00
  • Balanced −14%
  • Summarise −4%
  • Chat −1%
  • Code gen −7%
  • 1.0M → 262K context
Qwen3 235B A22B Thinking 2507 Qwen1413.8 +31.5$0.748
  • Balanced −79%
  • Summarise −82%
  • Chat −73%
  • Code gen −73%
  • Agentic −73%
  • 1.0M → 131K context
  • no image, file input
Inkling Small Thinking Machines1411.7 +29.4$0.637
  • Balanced −82%
  • Summarise −79%
  • Chat −84%
  • Code gen −84%
  • Agentic −82%
  • no file input
Qwen3 Max Qwen1412.7 +30.4$1.56
  • Balanced −55%
  • Summarise −60%
  • Chat −53%
  • Code gen −53%
  • Agentic −56%
  • 1.0M → 262K context
  • no image, file input
GPT-5.4 Mini OpenAI1412.1 +29.8$1.69
  • Balanced −52%
  • Summarise −60%
  • Chat −48%
  • Code gen −46%
  • Agentic −55%
  • 1.0M → 400K context
Qwen3.5-27B Qwen1407.9 +25.6$0.536
  • Balanced −85%
  • Summarise −86%
  • Chat −81%
  • Code gen −81%
  • Agentic −80%
  • 1.0M → 262K context
  • no file input
MiniMax M2.7 MiniMax1405.3 +23$0.525
  • Balanced −85%
  • Summarise −85%
  • Chat −85%
  • Code gen −85%
  • Agentic −85%
  • 1.0M → 205K context
  • no image, file input
Step 3.5 Flash StepFun1403.8 +21.5$0.150
  • Balanced −96%
  • Summarise −94%
  • Chat −95%
  • Code gen −96%
  • Agentic −94%
  • 1.0M → 262K context
  • no image, file input
o3 OpenAI1409.2 +26.9$3.50
  • Balanced same price
  • Summarise same price
  • Chat same price
  • Code gen same price
  • Agentic same price
  • 1.0M → 200K context
Qwen3.5-Flash Qwen1397.6 +15.3$0.114
  • Balanced −97%
  • Summarise −96%
  • Chat −96%
  • Code gen −97%
  • Agentic −95%
  • 1.0M → 1.0M context
  • no file input
Qwen3 VL 235B A22B Thinking Qwen1400.6 +18.3$1.30
  • Balanced −63%
  • Summarise −69%
  • Chat −53%
  • Code gen −53%
  • Agentic −53%
  • 1.0M → 131K context
  • no file input
GPT-5 OpenAI1405.6 +23.3$3.44
  • Balanced −2%
  • Summarise −27%
  • Agentic −6%
  • 1.0M → 400K context
Qwen3.5-35B-A3B Qwen1395.6 +13.3$0.500
  • Balanced −86%
  • Summarise −84%
  • Chat −84%
  • Code gen −84%
  • Agentic −80%
  • 1.0M → 262K context
  • no file input
Grok 4.3 xAI1397.5 +15.2$1.56
  • Balanced −55%
  • Summarise −46%
  • Chat −64%
  • Code gen −65%
  • Agentic −60%
  • 1.0M → 1.0M context
Claude Haiku 4.5 Anthropic1394.9 +12.6$2.00
  • Balanced −43%
  • Summarise −50%
  • Chat −41%
  • Code gen −39%
  • Agentic −47%
  • 1.0M → 200K context
Qwen3 30B A3B Instruct 2507 Qwen1384.3 tie$0.084
  • Balanced −98%
  • Summarise −97%
  • Chat −97%
  • Code gen −98%
  • Agentic −97%
  • 1.0M → 262K context
  • 33K → 32K max output
  • no image, file input
GLM 4.5 Air Z.ai1382.8 tie$0.310
  • Balanced −91%
  • Summarise −93%
  • Chat −90%
  • Code gen −90%
  • Agentic −91%
  • 1.0M → 131K context
  • no image, file input

What this compares, and what it leaves out

  • Quality is LMArena Elo, used under CC BY 4.0 from the official dataset. The 95% confidence interval on a difference between two scores is about ±10.68 points, so a gap smaller than that is marked tie rather than an improvement — see significance bands.
  • 188 further models at this delivery mode carry a price but no independent score. They are absent from the comparison in both directions — unrated is not a zero, and an unmeasured model is neither an alternative nor a worse buy.
  • Retired models are never offered as an alternative, and a model only competes against its own delivery mode: batch trades latency for price, so it is not a like-for-like swap.
  • Nothing here measures latency, throughput, rate limits or how a model behaves on your prompts. Two models with the same index score are not interchangeable.
  • The models that nothing beats on both axes are on the value frontier, and every other model something cheaper beats is listed here.