Cheaper alternatives to Qwen3 Max

Qwen LMArena 1412.7 $1.56/M on a balanced workload prices as of 2026-08-28

17 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, 33 score at least as high as Qwen3 Max and cost no more under at least one workload. 17 match or beat it on every capability we hold — context, maximum output, input modes, tool use and extended reasoning. 16 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 Qwen3 Max, it is not generated.

Where it holds

Workload	Qwen3 Max $/M	Better and cheaper	With a trade
Balanced	$1.56	17	16
Summarise	$0.758	17	16
Chat	$1.84	17	16
Code gen	$2.60	17	16
Agentic	$0.877	17	16

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

Intelligence	1412.7
Context window	262K
Max output	66K
Input modes	text
Tool use	yes
Extended reasoning	yes

A replacement has to clear every line above, not just the score. Full record for Qwen3 Max.

Better and cheaper, nothing given up 17

Each of these matches or beats Qwen3 Max on context, maximum output, input modes, tool use and reasoning, scores at least as high, and costs no more.

#	Model	Intelligence	$/M	Holds under
1	Gemini 3.7 Flash Google	1490.2 +77.5	$0.750	Balanced −52% Summarise −53% Chat −53% Code gen −52% Agentic −54%
2	Gemini 3.6 Flash Google	1476.5 +63.8	$1.50	Balanced −4% Summarise −7% Chat −5% Code gen −4% Agentic −9%
3	MiMo-V2.5-Pro Xiaomi	1465 +52.3	$0.544	Balanced −65% Summarise −56% Chat −74% Code gen −75% Agentic −72%
4	Qwen3.7 Plus Qwen	1456.2 +43.5	$0.560	Balanced −64% Summarise −61% Chat −66% Code gen −66% Agentic −64%
5	Hy3 Tencent	1441.2 +28.5	$0.144	Balanced −91% Summarise −90% Chat −91% Code gen −91% Agentic −91%
6	Kimi K2.5 Moonshot AI	1445.2 +32.5	$0.900	Balanced −42% Summarise −43% Chat −43% Code gen −42% Agentic −44%
7	Qwen3.8 27B Qwen	1440.8 +28.1	$0.956	Balanced −39% Summarise −43% Chat −36% Code gen −36% Agentic −38%
8	Qwen3.5 397B A17B Qwen	1438.3 +25.6	$0.877	Balanced −44% Summarise −36% Chat −36% Code gen −40% Agentic −22%
9	DeepSeek V4 Pro 0423 DeepSeek	1439.2 +26.5	$1.09	Balanced −30% Summarise −9% Chat −47% Code gen −49% Agentic −40%
10	Qwen3.6 Plus Qwen	1436.8 +24.1	$0.731	Balanced −53% Summarise −46% Chat −47% Code gen −50% Agentic −35%
11	MiniMax M3 MiniMax	1434.8 +22.1	$0.525	Balanced −66% Summarise −64% Chat −68% Code gen −68% Agentic −67%
12	Gemini 3.5 Flash Lite Google	1436.5 +23.8	$0.850	Balanced −46% Summarise −56% Chat −40% Code gen −39% Agentic −46%
13	DeepSeek V4 Flash 0423 DeepSeek	1431.6 +18.9	$0.101	Balanced −94% Summarise −91% Chat −95% Code gen −95% Agentic −94%
14	MiMo-V2.5 Xiaomi	1427.3 +14.6	$0.175	Balanced −89% Summarise −86% Chat −92% Code gen −92% Agentic −91%
15	GPT-5.6 Luna OpenAI	1428.5 +15.8	$0.450	Balanced −71% Summarise −74% Chat −70% Code gen −70% Agentic −72%
16	Qwen3.5-122B-A10B Qwen	1417.9 tie	$0.715	Balanced −54% Summarise −54% Chat −46% Code gen −48% Agentic −39%
17	Gemini 3.1 Flash Lite Preview Google	1414.8 tie	$0.563	Balanced −64% Summarise −67% Chat −63% Code gen −62% Agentic −65%

Cheaper and higher-scoring, but you give something up 16

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.

Model	Intelligence	$/M	Holds under	What you give up
Gemma 4 31B Google	1441.7 +29	$0.152	Balanced −90% Summarise −88% Chat −90% Code gen −91% Agentic −88%	66K → 16K max output
GLM 5 Z.ai	1445.2 +32.5	$0.930	Balanced −40% Summarise −30% Chat −47% Code gen −48% Agentic −42%	262K → 205K context
GLM 4.6 Z.ai	1439.8 +27.1	$0.875	Balanced −44% Summarise −39% Chat −47% Code gen −47% Agentic −44%	262K → 205K context
Gemma 4 26B A4B Google	1434.6 +21.9	$0.138	Balanced −91% Summarise −89% Chat −90% Code gen −91% Agentic −87%	66K → 16K max output
GLM 4.7 Z.ai	1435.3 +22.6	$0.738	Balanced −53% Summarise −50% Chat −54% Code gen −54% Agentic −53%	262K → 205K context
GLM 4.5 Z.ai	1429.4 +16.7	$1.00	Balanced −36% Summarise −29% Chat −41% Code gen −42% Agentic −37%	262K → 131K context
DeepSeek V3.2 DeepSeek	1424.6 +11.9	$0.290	Balanced −81% Summarise −70% Chat −85% Code gen −88% Agentic −77%	262K → 164K context
DeepSeek V3.2 Exp DeepSeek	1424.4 +11.7	$0.305	Balanced −80% Summarise −63% Chat −82% Code gen −86% Agentic −67%	262K → 164K context
R1 0528 DeepSeek	1427.9 +15.2	$0.912	Balanced −42% Summarise −29% Chat −39% Code gen −43% Agentic −25%	262K → 164K context 66K → 33K max output
Qwen3 235B A22B Instruct 2507 Qwen	1419.3 tie	$0.205	Balanced −87% Summarise −85% Chat −85% Code gen −86% Agentic −82%	66K → 16K max output no extended reasoning
Qwen3 VL 235B A22B Instruct Qwen	1420.9 tie	$0.632	Balanced −59% Summarise −65% Chat −54% Code gen −53% Agentic −55%	66K → 33K max output no extended reasoning
DeepSeek V3.1 Terminus DeepSeek	1419.6 tie	$0.453	Balanced −71% Summarise −65% Chat −72% Code gen −73% Agentic −66%	262K → 164K context 66K → 33K max output
Qwen3 Next 80B A3B Instruct Qwen	1418.6 tie	$0.350	Balanced −78% Summarise −81% Chat −73% Code gen −73% Agentic −74%	no extended reasoning
DeepSeek V3.1 DeepSeek	1419.1 tie	$0.825	Balanced −47% Summarise −20% Chat −46% Code gen −53% Agentic −18%	262K → 164K context
Gemini 2.5 Flash Google	1417.3 tie	$0.850	Balanced −46% Summarise −56% Chat −40% Code gen −39% Agentic −46%	66K → 66K max output
Qwen3 235B A22B Thinking 2507 Qwen	1413.8 tie	$0.748	Balanced −52% Summarise −56% Chat −43% Code gen −43% Agentic −38%	262K → 131K context

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.