o4 Mini High vs Qwen3.8 2.4T A95B
o4 Mini High costs 1.4x less per output token than Qwen3.8 2.4T A95B ($4.40 vs $6.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $4.40
- Coding
- No data
- Overall
- No data
- Output $/M
- $6.00
o4 Mini High or Qwen3.8 2.4T A95B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick o4 Mini High for output tokens 1.4x cheaper ($4.40 vs $6.00 per million).
No benchmark has tested both yet. o4 Mini High has results on ALE-Bench and GDPval; Qwen3.8 2.4T A95B on AA Coding Index, SciCode and AA Intelligence Index. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Qwen3.8 2.4T A95B has a AA Intelligence Index result, 39.9.
Directional only
Agentic work
AA Agentic Index
No call
Only Qwen3.8 2.4T A95B has a AA Agentic Index result, 50.1.
Directional only
Long documents
Listed context window
Qwen3.8 2.4T A95B
Qwen3.8 2.4T A95B takes 1.05M tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
o4 Mini High
o4 Mini High $0.0033, Qwen3.8 2.4T A95B $0.0050 per turn.
List prices
At a glance
- Coding index
- o4 Mini High not benchmarked, Qwen3.8 2.4T A95B not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- o4 Mini High $4.40 against Qwen3.8 2.4T A95B $6.00 per million output tokens, 1.4x apart.
- Context window
- o4 Mini High takes 200K tokens, Qwen3.8 2.4T A95B 1.05M.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index3 boards measured
| Benchmark | o4 Mini High | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 71.9 | Only Qwen3.8 2.4T A95B measured |
| SciCode | Not measured | 54.1% | Only Qwen3.8 2.4T A95B measured |
| ALE-Bench | 826.2 | Not measured | Only o4 Mini High measured |
| Neither model has a result on the other 36 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | o4 Mini High | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 39.9 | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | o4 Mini High | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.1 | Only Qwen3.8 2.4T A95B measured |
| GDPval | 25.3% | Not measured | Only o4 Mini High measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | o4 Mini High | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | Not measured | 93.5% | Only Qwen3.8 2.4T A95B measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 42.4% | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 20 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | o4 Mini High | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 80.3% | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 45 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
o4 Mini High costs less
Repository review
50K input + 3K output tokens
o4 Mini High costs less
Agent loop
200K input + 10K output tokens
o4 Mini High costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI o4 Mini High | Qwen3.8 2.4T A95B |
|---|---|---|
| Maker | OpenAI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | April 16, 2025 | August 12, 2026 |
| Context window | 200K | 1.05M |
| Input $/Mtok | $1.10 | $2.00 |
| Output $/Mtok | $4.40 | $6.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is o4 Mini High better than Qwen3.8 2.4T A95B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick o4 Mini High for output tokens 1.4x cheaper ($4.40 vs $6.00 per million).
Which is cheaper, o4 Mini High or Qwen3.8 2.4T A95B?
o4 Mini High costs $1.10 per million input tokens and $4.40 per million output tokens; Qwen3.8 2.4T A95B costs $2.00 and $6.00. Cost per solved task is known for neither of them.
Which has the bigger context window, o4 Mini High or Qwen3.8 2.4T A95B?
Qwen3.8 2.4T A95B, with 1.05M tokens against 200K.
Has any benchmark tested both o4 Mini High and Qwen3.8 2.4T A95B?
No benchmark has tested both yet. o4 Mini High has results on ALE-Bench and GDPval; Qwen3.8 2.4T A95B on AA Coding Index, SciCode and AA Intelligence Index. Compare them on price and context instead. Data as of October 22, 2026.