Compare / Qwen3-235B-A22B-Instruct-2507 vs Llama 3.2 1B Instruct

Qwen3-235B-A22B-Instruct-2507 vs Llama 3.2 1B Instruct

Which is cheaper, which is more capable, and which does better at each kind of work, from 24 results on 4 sources that measured both models.

AlibabaQwen3-235B-A22B-Instruct-2507 Released 21 Jul 2025 · $0.15 in · $0.75 out
MetaLlama 3.2 1B Instruct Released 25 Sep 2024 · $0.027 in · $0.20 out
Qwen3-235B-A22B-Instruct-2507 wins 24Llama 3.2 1B Instruct wins 0

Of the 24 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.

Results as of 9 October 2026 (catalogue release 2026-10-09-dd620e778ac5). See also Alibaba vs Meta, every model from both labs.

Qwen3-235B-A22B-Instruct-2507 or Llama 3.2 1B Instruct? The short answer

Pick Qwen3-235B-A22B-Instruct-2507 if quality matters most: it scores higher (Intelligence Index 12.0 against 4.8). Pick Llama 3.2 1B Instruct if cost matters more: it costs 4.3 times less per token.

  • Llama 3.2 1B Instruct is cheaper: $0.071 against $0.30 per million tokens, 4.3 times less.
  • Qwen3-235B-A22B-Instruct-2507 scores higher on the Artificial Analysis Intelligence Index: 12.0 against 4.8.
  • Qwen3-235B-A22B-Instruct-2507 is newer: released 21 Jul 2025, against 25 Sep 2024 for Llama 3.2 1B Instruct.
  • On third-party benchmarks, on the results both models have: Qwen3-235B-A22B-Instruct-2507 does better for agents and tool use, reasoning and knowledge and writing.

Head to head

12.0
Intelligence Index
4.8
$0.30
Price per million tokens, blendedlower is better
$0.071
262,144
Context window, tokens
60,000

Every fact side by side

Qwen3-235B-A22B-Instruct-2507Llama 3.2 1B Instruct
Price per million tokens$0.15 in · $0.75 out$0.027 in · $0.20 out
Blended (3 in : 1 out)$0.30$0.071
Cheapest host, blended$0.15 (GMICloud, FP8)–
Intelligence Index12.04.8
Spring Prompt overall––
Output speed, tokens a second––
Context window262,144 tokens60,000 tokens
Released21 Jul 2025 (newer)25 Sep 2024
WeightsOpenOpen
Developer based inChinathe US

Prices are the developer's list price where we have read it, otherwise the typical host on OpenRouter; see every model's price. Intelligence and speed from Artificial Analysis.

Which is better for what

Each model's rank among the models on sale today, for each kind of work, from our own benchmarks and licensed sources. Further right is better; the better rank is in green.

Agents and tool useMulti-step tasks with tools: support desks, coding agents, function calls 51 of 164 164 of 164
Reasoning and knowledgeHard questions across science, maths and general knowledge 129 of 198 192 of 198
WritingWhat people prefer in blind comparisons, and judged writing quality 85 of 188 187 of 188
Sticking to the factsSummarising without inventing things, and factual answers 98 of 152 not measured

Every shared result

Each model's best result on every measure both have, grouped by benchmark, with the setting that produced it. Under each measure, every model that benchmark has measured is a grey tick, best to the right, so you can see where the two sit in the field. The headline measures of each benchmark come first; the rest are under "Show all". Green marks the better value; where a source reports ranges that overlap, neither is marked.

MeasureQwen3-235B-A22B-Instruct-2507Llama 3.2 1B Instruct
Arena (formerly LMArena) reported by Arena (formerly LMArena) · 3 results
Overall · TextArena rating, higher is better 109 · 369 of 387 measured 1,422 1,111
Business, management and finance · TextArena rating, higher is better 97 · 367 of 380 measured 1,432 1,070
Creative writing · TextArena rating, higher is better 122 · 366 of 385 measured 1,378 1,083
Artificial Analysis reported by Artificial Analysis · 3 results
Artificial Analysis Intelligence Indexindex score, higher is better 153 · 240 of 243 measured 12.0 4.8
GPQA Diamond% of questions, higher is better 136 · 231 of 231 measured 75.3% 19.6%
Humanity's Last Exam% of questions, higher is better 144 · 184 of 242 measured 11.1% 5.5%
Berkeley Function Calling Leaderboard (BFCL) V4 reported by Berkeley Function Calling Leaderboard (BFCL) V4 · 3 results
Overall accuracy · BFCL% correct, higher is better 20 · 79 of 81 measured 52.2%bfcl prompt 10.8%bfcl fc
Irrelevance detection · BFCL% correct, higher is better 41 · 74 of 81 measured 81.7%bfcl fc 51.6%bfcl fc
Memory · BFCL% correct, higher is better 26 · 68 of 81 measured 23.9%bfcl fc 3.2%bfcl fc
UGI Leaderboard reported by UGI Leaderboard · 3 results
Writing score · UGIscore out of 100, higher is better 80 · 223 of 230 measured 49.0 11.8
Requested-length error · UGI% off the requested word count, lower is better 69 · 129 of 230 measured 15.0% 22.0%
Style adherence · UGIscore from 0 to 1, higher is better 64 · 140 of 230 measured 0.36 0.33
Show all 24 results (12 more)
MeasureQwen3-235B-A22B-Instruct-2507Llama 3.2 1B Instruct
Arena (formerly LMArena) reported by Arena (formerly LMArena) · 3 results
Expert prompts · TextArena rating, higher is better 103 · 338 of 338 measured 1,447 1,082
Instruction following · TextArena rating, higher is better 104 · 368 of 387 measured 1,414 1,086
Writing, literature and language · TextArena rating, higher is better 115 · 370 of 386 measured 1,396 1,076
Artificial Analysis reported by Artificial Analysis · 4 results
IFBench% of instructions, higher is better 113 · 193 of 195 measured 46.1% 22.8%
Long-context reasoning (AA-LCR)% of questions, higher is better 177 · 218 of 233 measured 33.9% 6.7%
Terminal-Bench Hard% of tasks, higher is better 110 · 185 of 190 measured 15.2% 0.0%
τ²-bench telecom% of tasks, higher is better 127 · 188 of 193 measured 33.3% 0.0%
Berkeley Function Calling Leaderboard (BFCL) V4 reported by Berkeley Function Calling Leaderboard (BFCL) V4 · 5 results
Multi-turn tasks · BFCL% correct, higher is better 20 · 77 of 81 measured 45.4%bfcl fc 0.0%bfcl fc
Relevance detection · BFCL% correct, higher is better 8 · 77 of 81 measured 93.8%bfcl prompt 43.8%bfcl fc
Single-turn calls (curated) · BFCL% correct, higher is better 2 · 76 of 81 measured 90.3%bfcl prompt 38.4%bfcl fc
Single-turn calls (user-contributed) · BFCL% correct, higher is better 15 · 78 of 81 measured 78.7%bfcl prompt 11.8%bfcl fc
Web search · BFCL% correct, higher is better 20 · 66 of 81 measured 54.0%bfcl fc 0.0%bfcl fc

Quick answers

Is Qwen3-235B-A22B-Instruct-2507 better than Llama 3.2 1B Instruct?

Pick Qwen3-235B-A22B-Instruct-2507 if quality matters most: it scores higher (Intelligence Index 12.0 against 4.8). Pick Llama 3.2 1B Instruct if cost matters more: it costs 4.3 times less per token.

Which is cheaper, Qwen3-235B-A22B-Instruct-2507 or Llama 3.2 1B Instruct?

Llama 3.2 1B Instruct is cheaper: $0.071 against $0.30 per million tokens, 4.3 times less.

Which is better for agents and tool use, Qwen3-235B-A22B-Instruct-2507 or Llama 3.2 1B Instruct?

Qwen3-235B-A22B-Instruct-2507 ranks 51 of 164 models on sale for multi-step tasks with tools: support desks, coding agents, function calls, against 164 for Llama 3.2 1B Instruct.

Which is better for reasoning and knowledge, Qwen3-235B-A22B-Instruct-2507 or Llama 3.2 1B Instruct?

Qwen3-235B-A22B-Instruct-2507 ranks 129 of 198 models on sale for hard questions across science, maths and general knowledge, against 192 for Llama 3.2 1B Instruct.

Which is better for writing, Qwen3-235B-A22B-Instruct-2507 or Llama 3.2 1B Instruct?

Qwen3-235B-A22B-Instruct-2507 ranks 85 of 188 models on sale for what people prefer in blind comparisons, and judged writing quality, against 187 for Llama 3.2 1B Instruct.

Which has the bigger context window, Qwen3-235B-A22B-Instruct-2507 or Llama 3.2 1B Instruct?

Qwen3-235B-A22B-Instruct-2507: 262,144 tokens, against 60,000 for Llama 3.2 1B Instruct.

Run Qwen3-235B-A22B-Instruct-2507 and Llama 3.2 1B Instruct on your own prompt

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