Qwen3 235B-A22B Instruct 2507 vs Qwen3 14B
Qwen3 235B-A22B Instruct 2507 comes out ahead, 58 to 54 on our weighted score, and it is the cheaper option too.
- Our pick
Alibaba (Qwen)
Qwen3 235B-A22B Instruct 2507
58/100- ECI138.9
- Price$0.15 / $0.75
- Context262K
Alibaba (Qwen)
Qwen3 14B
54/100- ECI138.2
- Price$0.35 / $1.40
- Context131K
Add a model
Make it a three-way comparison.
Qwen3 235B-A22B Instruct 2507 is our pick
Qwen3 235B-A22B Instruct 2507 is the better all-round choice, scoring 58/100 against Qwen3 14B (54). It leads on price and context window. Qwen3 14B wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityQwen3 235B-A22B Instruct 2507Capabilities Index (ECI): Qwen3 235B-A22B Instruct 2507 138.9 · Qwen3 14B 138.2
- Lowest priceQwen3 235B-A22B Instruct 2507Qwen3 235B-A22B Instruct 2507 $0.30 · Qwen3 14B $0.613 per 1M tokens (3:1 blend)
- Longest contextQwen3 235B-A22B Instruct 2507Qwen3 235B-A22B Instruct 2507 262,144 · Qwen3 14B 131,072 tokens
- Widest inputsSame inputsQwen3 235B-A22B Instruct 2507: Text · Qwen3 14B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Qwen3 235B-A22B Instruct 2507 | Qwen3 14B |
|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 64 | 63 |
| Price | 25% | 75 | 60 |
| Inputs & features | 15% | 25 | 35 |
| Context window | 10% | 37 | 24 |
| Overall | 100% | 58/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | ||
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | 138.9 (best) | 138.2 |
| ECI rank | #105 of 148 (best) | #107 of 148 |
| GPQA DiamondGraduate-level science questions | — | 63.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 66.4% |
| Price per million tokens | ||
| Input | $0.15 (best) | $0.35 |
| Output | $0.75 (best) | $1.40 |
| Cached input | — | — |
| Blended (3:1) | $0.30 (best) | $0.613 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 11 providers | Official Alibaba API |
| Limits | ||
| Context window | 262,144 tokens (best) | 131,072 tokens |
| Max output | 16,384 tokens (best) | 8,192 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | OpenApache 2.0 | Open |
| API model ID | — | qwen3-14b |
| API providers | 11 (best) | 1 |
| Released | Jul 21, 2025 | Apr 29, 2025 |
| Knowledge cutoff | — | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
Qwen3 235B-A22B Instruct 2507$3.00
Qwen3 14B$6.30
Which should you choose?
Which is better: Qwen3 235B-A22B Instruct 2507 or Qwen3 14B?
Qwen3 235B-A22B Instruct 2507 is the better all-round choice, scoring 58/100 against Qwen3 14B (54). It leads on price and context window. Qwen3 14B wins on inputs & features. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Qwen3 235B-A22B Instruct 2507 or Qwen3 14B?
Qwen3 235B-A22B Instruct 2507 is cheaper at $0.15 input / $0.75 output per million tokens (median across 11 API providers). Qwen3 14B costs $0.35 input / $1.40 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $0.30 per million tokens for Qwen3 235B-A22B Instruct 2507 versus $0.613 for Qwen3 14B (2× as much).
Which scores higher on benchmarks?
Qwen3 235B-A22B Instruct 2507 scores higher on the Capabilities Index (ECI): Qwen3 235B-A22B Instruct 2507 138.9 (#105 of 148) and Qwen3 14B 138.2 (#107 of 148). The confidence ranges of the top two overlap (135.8–140.6 vs 133.5–140.1), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 235B-A22B Instruct 2507 and Qwen3 14B yet, so there is no like-for-like coding score. On overall capability, Qwen3 235B-A22B Instruct 2507 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.
Which has the bigger context window?
Qwen3 235B-A22B Instruct 2507 has the largest context window at 262,144 tokens, against 131,072 for Qwen3 14B. Maximum output per response: Qwen3 235B-A22B Instruct 2507 up to 16,384, Qwen3 14B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Qwen3 235B-A22B Instruct 2507 accepts text; Qwen3 14B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (Apache 2.0), so you can self-host them.
Which is newer?
Qwen3 235B-A22B Instruct 2507 is the newest, released Jul 21, 2025. Qwen3 14B came out Apr 29, 2025. Knowledge cutoff: Qwen3 14B Apr 2025.
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.