March 17, 2025
Alibaba Cloud's QwQ-32B is a groundbreaking compact reasoning model that challenges conventional wisdom in AI development. With just 32 billion parameters—20 times fewer than DeepSeek-R1's 671 billion—it delivers performance comparable to leading models in mathematical reasoning, coding, and multi-step problem-solving. Built on the Qwen2.5-32B foundation model and enhanced with Reinforcement Learning (RL), QwQ-32B exemplifies how efficient training and agent integration can bridge the gap between smaller and larger models.
QwQ-32B leverages Qwen2.5-32B as its base model, which was pre-trained on extensive world knowledge. The model's core innovation lies in its RL-driven training, where rewards from general reward models and rule-based verifiers refine its reasoning, coding, and alignment with human preferences. This approach enables it to adapt dynamically to environmental feedback, think critically, and utilize tools effectively.
Here's a demonstration of QwQ-32B's reasoning capabilities using Ollama:
bash
$ ollama pull qwq:latest
pulling manifest
pulling 7ccc6415b2c7... 100% ▕▏ 19 GB
pulling 41190096a061... 100% ▕▏ 1.2 KB
pulling d18a5cc71b84... 100% ▕▏ 11 KB
pulling e5229acc2492... 100% ▕▏ 120 B
pulling 1972e9972e2e... 100% ▕▏ 488 B
verifying sha256 digest
writing manifest
removing unused layers
success
$ ollama run "How many s's are in the word Mississippi?"
<think>
Okay, so I need to figure out how many times the letter 's' appears in the word "Mississippi". Hmm, let me start by writing down
the word and looking at each letter one by one. Let me spell it out: M-I-S-S-I-S-S-I-P-P-I.
Wait a second, maybe I should write it again to make sure I have all the letters right. Yeah, that's correct: M, I, S, S, I, S,
S, I, P, P, I. Let me count how many letters there are in total first. Starting with M as 1, then each subsequent letter adds
one... so that would be 1 (M), 2 (I), 3 (S), 4 (S), 5 (I), 6 (S), 7 (S), 8 (I), 9 (P), 10 (P), 11 (I). So there are 11 letters
in total.
Now, focusing on the letter 's'. Let me go through each position again:
1. M - not an S
2. I - not an S
3. S - that's one S
4. S - another S, so two now
5. I - nope
6. S - third S
7. S - fourth S
8. I - still no
9. P - no
10. P - nope again
11. I - last letter isn't an S
So adding those up: positions 3,4,6,7 are S's. That makes four? Wait, but let me check again because sometimes when counting I
might make a mistake.
Breaking it down:
- After the first two letters (M and I), we hit the third letter which is S.
- The fourth is also an S.
- Then after that comes I, then another S at position 6.
- Position 7 is another S.
- From there until the end, no more S's.
So positions: 3,4,6,7. That's four instances of 's'.
But wait, hold on a second... Maybe I miscounted? Let me try another approach. Let's write out all letters with their counts:
Letters in Mississippi:
M:1
I:4 (because there are Is at positions 2,5,8,11)
S: ?
P:2
Wait, so if the total letters add up to 11, then M + I(4) + S(some number) + P(2). So 1+4=5; plus 2 for Ps is 7. The remaining
must be S's. Since total is 11, then S count would be 11 - (1+4+2)= 11-7=4. Therefore, S occurs four times.
Hmm that matches my previous count. So the answer should be 4?
Wait but sometimes people might confuse with the spelling. Let me confirm the word again: M-I-S-S-I-S-S-I-P-P-I.
Yes, so between the Ms and Is and Ps, there are four S's.
Alternatively, maybe I can think of it as "Mississippi" is a well-known example in combinatorics for permutations with repeated
elements. The standard breakdown is:
Letters: M (1), I(4), S(4), P(2). So the count for S is indeed 4.
Therefore, the number of 's's in Mississippi should be four.
</think>
The word "Mississippi" consists of the letters: M, I, S, S, I, S, S, I, P, P, I.
Let's count each occurrence of the letter s:
1. The third letter is S
2. The fourth letter is S
3. The sixth letter is S
4. The seventh letter is S
Thus, there are 4 s's in "Mississippi".
Answer: 4
QwQ-32B represents a paradigm shift in AI development, proving that size isn't everything. By combining RL with a robust foundation model and agent capabilities, Alibaba Cloud has created a model that competes with industry giants while remaining accessible and affordable. Its open-source release ensures widespread adoption, driving innovation in areas like education, coding assistance, and adaptive AI agents.
