ZMIME
Comparison · 3 models · Updated Oct 4, 2026

GPT OSS 120B vs Llama 4 Maverick 17B Instruct vs Qwen3 235B-A22B Instruct 2507

GPT OSS 120B comes out ahead, 61 to 58 and 58 on our weighted score, and it is the cheaper option too.

  1. Our pick

    OpenAI

    GPT OSS 120B

    Released Aug 5, 2025

    61/100
    • ECI140.0
    • Price$0.15 / $0.60
    • Context131K
  2. Meta

    Llama 4 Maverick 17B Instruct

    Released Apr 5, 2025

    58/100
    • ECI132.2
    • Price$0.321 / $0.91
    • Context1M
  3. Alibaba (Qwen)

    Qwen3 235B-A22B Instruct 2507

    Released Jul 21, 2025

    58/100
    • ECI138.9
    • Price$0.15 / $0.75
    • Context262K
01 — Verdict

GPT OSS 120B is our pick

GPT OSS 120B is the better all-round choice, scoring 61/100 against Qwen3 235B-A22B Instruct 2507 (58) and Llama 4 Maverick 17B Instruct (58). It leads on price. Llama 4 Maverick 17B Instruct wins on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityGPT OSS 120BCapabilities Index (ECI): GPT OSS 120B 140.0 · Qwen3 235B-A22B Instruct 2507 138.9 · Llama 4 Maverick 17B Instruct 132.2
  • Lowest priceGPT OSS 120BGPT OSS 120B $0.263 · Qwen3 235B-A22B Instruct 2507 $0.30 · Llama 4 Maverick 17B Instruct $0.468 per 1M tokens (3:1 blend)
  • Longest contextLlama 4 Maverick 17B InstructLlama 4 Maverick 17B Instruct 1,000,000 · Qwen3 235B-A22B Instruct 2507 262,144 · GPT OSS 120B 131,072 tokens
  • Widest inputsLlama 4 Maverick 17B InstructGPT OSS 120B: Text · Llama 4 Maverick 17B Instruct: Text, Images · Qwen3 235B-A22B Instruct 2507: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGPT OSS 120BLlama 4 Maverick 17B InstructQwen3 235B-A22B Instruct 2507
CapabilityCapabilities Index (ECI)50%655664
Price25%776675
Inputs & features15%455025
Context window10%246037
Overall100%61/10058/10058/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

GPT OSS 120B vs Llama 4 Maverick 17B Instruct vs Qwen3 235B-A22B Instruct 2507 specifications side by side
SpecificationGPT OSS 120BOpenAILlama 4 Maverick 17B InstructMetaQwen3 235B-A22B Instruct 2507Alibaba (Qwen)
Capability
Capabilities Index (ECI)140.0 (best)132.2138.9
ECI rank#99 of 148 (best)#122 of 148#105 of 148
GPQA DiamondGraduate-level science questions75.8% (best)67.0%—
OTIS Mock AIME 2024–2025Competition mathematics88.9% (best)20.6%—
Price per million tokens
Input$0.15 (best)$0.321$0.15 (best)
Output$0.60 (best)$0.91$0.75
Cached input———
Blended (3:1)$0.263 (best)$0.468$0.30
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 36 providersMedian of 6 providersMedian of 11 providers
Limits
Context window131,072 tokens1,000,000 tokens (best)262,144 tokens
Max output32,768 tokens (best)16,384 tokens16,384 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningYesNoNo
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsOpenOpenOpenApache 2.0
API model ID———
API providers39 (best)611
ReleasedAug 5, 2025Apr 5, 2025Jul 21, 2025
Knowledge cutoff—Aug 2024—
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • GPT OSS 120B$2.70
  • Llama 4 Maverick 17B Instruct$5.03
  • Qwen3 235B-A22B Instruct 2507$3.00
04 — Questions

Which should you choose?

Which is better: GPT OSS 120B, Llama 4 Maverick 17B Instruct or Qwen3 235B-A22B Instruct 2507?

GPT OSS 120B is the better all-round choice, scoring 61/100 against Qwen3 235B-A22B Instruct 2507 (58) and Llama 4 Maverick 17B Instruct (58). It leads on price. Llama 4 Maverick 17B Instruct wins on inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, GPT OSS 120B, Llama 4 Maverick 17B Instruct or Qwen3 235B-A22B Instruct 2507?

GPT OSS 120B is cheaper at $0.15 input / $0.60 output per million tokens (median across 36 API providers). Qwen3 235B-A22B Instruct 2507 costs $0.15 input / $0.75 output per million tokens (median across 11 API providers); Llama 4 Maverick 17B Instruct costs $0.321 input / $0.91 output per million tokens (median across 6 API providers). At a typical mix of three input tokens to one output token, that is $0.263 per million tokens for GPT OSS 120B versus $0.30 for Qwen3 235B-A22B Instruct 2507 (1.1× as much) and $0.468 for Llama 4 Maverick 17B Instruct (1.8× as much).

Which scores higher on benchmarks?

GPT OSS 120B scores higher on the Capabilities Index (ECI): GPT OSS 120B 140.0 (#99 of 148), Qwen3 235B-A22B Instruct 2507 138.9 (#105 of 148) and Llama 4 Maverick 17B Instruct 132.2 (#122 of 148). The confidence ranges of the top two overlap (135.3–142.3 vs 135.8–140.6), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for GPT OSS 120B, Llama 4 Maverick 17B Instruct and Qwen3 235B-A22B Instruct 2507 yet, so there is no like-for-like coding score. On overall capability, GPT OSS 120B leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.

Which has the bigger context window?

Llama 4 Maverick 17B Instruct has the largest context window at 1,000,000 tokens, against 262,144 for Qwen3 235B-A22B Instruct 2507 and 131,072 for GPT OSS 120B. Maximum output per response: GPT OSS 120B up to 32,768, Llama 4 Maverick 17B Instruct up to 16,384, Qwen3 235B-A22B Instruct 2507 up to 16,384 tokens.

Which can read images, PDFs, audio or video?

GPT OSS 120B accepts text; Llama 4 Maverick 17B Instruct accepts text and images; Qwen3 235B-A22B Instruct 2507 accepts text. Llama 4 Maverick 17B Instruct handles the widest range of inputs.

Are any of these open source?

Yes, all three publish their weights (Apache 2.0), so you can self-host them.

Which is newer?

GPT OSS 120B is the newest, released Aug 5, 2025. Qwen3 235B-A22B Instruct 2507 came out Jul 21, 2025; Llama 4 Maverick 17B Instruct came out Apr 5, 2025. Knowledge cutoff: Llama 4 Maverick 17B Instruct Aug 2024.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.