Qwen2.5 7B Instruct vs Qwen3.8 2.4T A95B
Qwen2.5 7B Instruct costs 30.0x less per output token than Qwen3.8 2.4T A95B ($0.20 vs $6.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.20
- Coding
- No data
- Overall
- No data
- Output $/M
- $6.00
Qwen2.5 7B Instruct 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 Qwen2.5 7B Instruct for output tokens 30.0x cheaper ($0.20 vs $6.00 per million).
No benchmark has tested both yet. Qwen2.5 7B Instruct has results on Epoch Capabilities Index, BALROG and GPQA Diamond (Epoch AI run); 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 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen2.5 7B Instruct
Qwen2.5 7B Instruct $0.0002, Qwen3.8 2.4T A95B $0.0050 per turn.
List prices
At a glance
- Coding index
- Qwen2.5 7B Instruct 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
- Qwen2.5 7B Instruct $0.20 against Qwen3.8 2.4T A95B $6.00 per million output tokens, 30.0x apart.
- Context window
- Qwen2.5 7B Instruct takes 33K 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 Index2 boards measured
| Benchmark | Qwen2.5 7B Instruct | 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 |
| Neither model has a result on the other 41 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen2.5 7B Instruct | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 39.9 | Only Qwen3.8 2.4T A95B measured |
| Epoch Capabilities Index | 118.5 | Not measured | Only Qwen2.5 7B Instruct measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Qwen2.5 7B Instruct | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 50.1 | Only Qwen3.8 2.4T A95B measured |
| BALROG | 7.8% | Not measured | Only Qwen2.5 7B Instruct measured |
| MCP Atlas | Not measured | 84.5% | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 39 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Qwen2.5 7B Instruct | 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 |
| GPQA Diamond (Epoch AI run) | 35.5% | Not measured | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 20 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | Qwen2.5 7B Instruct | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| OTIS Mock AIME | 2.5% | Not measured | Only Qwen2.5 7B Instruct measured |
| MathArena | Not measured | 31.6% | Only Qwen3.8 2.4T A95B measured |
| Neither model has a result on the other 12 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Qwen2.5 7B Instruct | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| MMLU | 72.9% | Not measured | Only Qwen2.5 7B Instruct measured |
| Neither model has a result on the other 19 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Qwen2.5 7B Instruct | Qwen3.8 2.4T A95B | Leader |
|---|---|---|---|
| Long context reasoning (AA-LCR) | Not measured | 80.3% | Only Qwen3.8 2.4T A95B measured |
| DTBench | 47.7% | Not measured | Only Qwen2.5 7B Instruct measured |
| LMCA | 6.4% | Not measured | Only Qwen2.5 7B Instruct 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
Qwen2.5 7B Instruct costs less
Repository review
50K input + 3K output tokens
Qwen2.5 7B Instruct costs less
Agent loop
200K input + 10K output tokens
Qwen2.5 7B Instruct 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 | Qwen2.5 7B Instruct | Qwen3.8 2.4T A95B |
|---|---|---|
| Maker | Qwen | Qwen |
| Weights | Open weights | Open weights |
| Released | October 16, 2024 | August 12, 2026 |
| Context window | 33K | 1.05M |
| Input $/Mtok | $0.10 | $2.00 |
| Output $/Mtok | $0.20 | $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 Qwen2.5 7B Instruct 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 Qwen2.5 7B Instruct for output tokens 30.0x cheaper ($0.20 vs $6.00 per million).
Which is cheaper, Qwen2.5 7B Instruct or Qwen3.8 2.4T A95B?
Qwen2.5 7B Instruct costs $0.10 per million input tokens and $0.20 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, Qwen2.5 7B Instruct or Qwen3.8 2.4T A95B?
Qwen3.8 2.4T A95B, with 1.05M tokens against 33K.
Has any benchmark tested both Qwen2.5 7B Instruct and Qwen3.8 2.4T A95B?
No benchmark has tested both yet. Qwen2.5 7B Instruct has results on Epoch Capabilities Index, BALROG and GPQA Diamond (Epoch AI run); 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.