I was hyped for Nemotron 3 4B and it completely disappointed me compared to Qwen 3.5 4B

So I have been running some pretty demanding benchmarks on local models lately, and last week I posted results showing that Qwen 3.5 4B Q8 passed every single one of my custom tests. I was genuinely impressed. Then Nemotron 3 4B dropped today and I immediately grabbed the Q8 quant to put it through the same gauntlet. Spoiler: it did not go well.

The thing that had me excited about Nemotron was its different architecture, which supposedly allows for much larger context windows. That sounded promising on paper. Unfortunately, raw context capacity means nothing if the model cannot reason correctly inside that context.

Here is every test I ran, the exact prompts, and what each model actually produced.

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TEST 1: Dense multi-part math and structured output

The prompt asked the model to:

Define S(n) = sum from k=0 to n of (-1)^k times C(n,k) divided by (k+1)^2. Give a closed form in terms of H_{n+1}, evaluate S(2026), and prove it in at most 8 lines using integrals. Then compute T = sum from k=1 to 2026 of floor((17k+8)/29) minus floor((17k-4)/29) using purely modular justification. Then describe a Möbius + inclusion-exclusion algorithm for counting coprime pairs in a dynamic array, with pseudocode in exactly 14 lines where no variable name exceeds 8 characters. Then compute C(4052, 2026) mod 7 using Lucas theorem by converting to base 7. Then write a Portuguese paragraph of exactly 47 words, no digits, exactly one comma, containing "Möbius", "inclusão-exclusão" and "Lucas", ending with "fim." Wrap everything in one valid JSON.

Qwen 3.5 4B Q8 (correct):

json { "A": { "closed_form": "H_{n+1}/(n+1)", "value_2026": "H_{2027}/2027", "proof_8_lines": "S(n) = sum (-1)^k C(n,k) int_0^1 x^k(-ln x)dx\nSwap sum and integral: -int_0^1 ln(x)(1-x)^n dx\nLet u=1-x: S(n) = -int_0^1 u^n ln(1-u) du\nUsing identity int_0^1 x^n ln(1-x)dx = -H_{n+1}/(n+1)\nWe find S(n) = H_{n+1}/(n+1) for all n>=0\nFor n=2026, value is H_{2027}/2027 exactly.\nQED." }, "B": { "value": 838, "justification": "Difference is 1 iff (17k-4) mod 29 >= 17. gcd(17,29)=1 so residues cycle every 29 terms. Per period, 12 values qualify. 2026 = 69*29 + 25. Full periods: 69*12=828. Remainder k=1..25: residues for k=26..29 include two >= 17, so remainder adds 10. Total: 838." }, "C": { "idea": "Möbius inversion: coprime pairs = sum mu(d)*C(cnt[d],2). Maintain cnt per divisor, update incrementally.", "pseudocode": ["Precompute mu and divisors for V=1e6", "...14 lines total..."], "complexity": "O(max_divisors * (N+Q))" }, "D": { "base7_4052": "(14546)_7", "base7_2026": "(05623)_7", "lucas": "Digit pair (4,5) gives C(4,5)=0, so product is 0.", "mod7": 0 }, "E": { "resumo_47_palavras": "...exactly 47 words, one comma, no digits, ends with fim." } }

Every sub-task correct. Clean JSON. Math checks out.

Nemotron 3 nano 4B Q8 (wrong):

json { "A": { "forma_fechada": "H_{n+1}/(n+1)", "valor_2026": "H_{2027}/2027", "prova_8_linhas": "...mangled integral steps, wrong substitution..." }, "B": { "valor": 838, "justificativa": "Period 29 with 12 hits... 69 cycles = 828, remainder = 10" }, "C": { "pseudocodigo": ["read n", "a = []", "mu = [0]*(max+1)", "for i in range(n): a.append(int(input()))", "for x in a:", " for d in range(1,int(sqrt(x))):", " if x%d==0", " mu[d]+=1", " mu[x//d]-=1", "#", "#", "#", "#", "#", "#", "#"], "complexidade": "O(n√max)" }, "D": { "base7_4052": "14546", "base7_2026": "05623", "mod7": 0 }, "E": { "resumo_47_palavras": "Möbius inclusão-exclusão Lucas explica como contar pares coprimos em arrays dinâmicos, prática de programação que utiliza funções matemáticas para gerar contagem rápida e exibir resultados sem erros preciso de fim." } }

The pseudocode for part C was padded with 6 lines of just "#" to reach 14 lines. The proof in part A had wrong substitution steps. Part E had no digits but the comma placement was wrong and word count was off. It got lucky on a few numerical answers but failed the reasoning and format behind almost everything.

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TEST 2: Full algorithmic design with C++17

The prompt asked for:

An offline algorithm for range coprime pair queries with point updates, faster than O(q times V) and O(q times sqrt(V)). Must explicitly use Mo's algorithm with modifications (3D Mo) and Möbius inclusion-exclusion. Must include 24 pseudocode lines as a JSON array (each under 70 chars, variable names under 8 chars) and a full C++17 implementation under 220 lines with no recursion. Compute exact outputs for: n=5, A=[6,10,15,7,9], queries Q 1 5 / U 2 21 / Q 2 5 / U 5 25 / Q 1 3 / Q 3 5.

Qwen 3.5 4B Q8 (correct): Described 3D Mo clearly with incremental add/remove using divisor lists and Möbius weights. Produced all 24 pseudocode lines within the character and variable name limits. C++17 code was logically correct and compilable. Example outputs: [5, 2, 0, 2].

Nemotron 3 nano 4B Q8 (wrong): The JSON had malformed arrays. The C++ code had syntax errors and undefined variable references and would not compile. The pseudocode had 16 real lines and 8 "#" padding lines. The example outputs were wrong.

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TEST 3: Pattern compression inference

The prompt was simply:

11118888888855 → 118885 | 79999775555 → 99755 | AAABBBYUDD → ?

Qwen 3.5 4B Q8 (correct):

Correctly identified the rule as floor(count / 2) for each character, preserving input order. Showed the working: - A appears 3 times → floor(3/2) = 1 - B appears 3 times → floor(3/2) = 1 - Y appears 1 time → floor(1/2) = 0 (removed) - U appears 1 time → floor(1/2) = 0 (removed) - D appears 2 times → floor(2/2) = 1

Answer: ABD

Nemotron 3 nano 4B Q8 (wrong):

Answered AABBBY, showing it had no real understanding of the rule and was pattern-matching superficially without reasoning through the character counts.

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TEST 4: UI and frontend generation

I asked both to generate a business dashboard and a SaaS landing page with pricing. The screenshot comparison says everything.

Qwen produced a fully structured dashboard with labeled KPI cards (Revenue, Orders, Refunds, Conversion Rate), a smooth area chart, a donut chart for traffic sources, and a complete landing page with three pricing tiers at R$29, R$79, and R$199 with feature lists and styled buttons.

Nemotron produced an almost empty layout with two placeholder numbers and no charts, and a landing page that was a purple gradient with a single button and the same testimonial card duplicated twice. It looks like a template that forgot to load its content.

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Overall verdict

Nemotron 3 nano 4B Q8 failed all four tests. Qwen 3.5 4B Q8 passed all four last week. The architecture novelty that enables larger contexts did not translate into better reasoning, instruction following, structured output, or code generation. If you are picking between these two for local use right now it is not even a close call.

Full Qwen results from last week in the comments.