DeepSeek provider: prompt_cache_miss_tokens not mapped to cache.write #35974

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1. github-actions

   assigned

   jlongster

   on Jul 8, 2026
2. github-actions commented on Jul 8, 2026

   

   github-actionsBot

   on Jul 8, 2026 – with GitHub Actions

   Contributor

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   This issue might be a duplicate of or related to an existing issue. Please check:

   • OpenAI-compatible providers report zero tokens_cache_read despite upstream returning cached_tokens #34022: OpenAI-compatible providers report zero tokens_cache_read — similarly touches cache token accounting for DeepSeek/compatible providers, though that issue focuses on cache read tokens rather than cache.write / prompt_cache_miss_tokens.
3. Zaczero commented on Aug 18, 2026

   

   Zaczero

   on Aug 18, 2026

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   This is the same gap as #36749, in the same function, and the two are one patch rather than two.

   On V2 (0.0.0-beta-17498) the DeepSeek route goes through the shared OpenAI Chat protocol —
   openai-compatible-chat.ts reuses OpenAIChat.protocol end to end — and the mapping reads cache
   counts only from prompt_tokens_details:

   opencode/packages/ai/src/protocols/openai-chat.ts

   Lines 582 to 600 in 39be159

   	const mapUsage = (usage: OpenAIChatEvent["usage"]): Usage | undefined => {
   	if (!usage) return undefined
   	const input = usage.prompt_tokens ?? undefined
   	const output = usage.completion_tokens ?? undefined
   	const cached = usage.prompt_tokens_details?.cached_tokens ?? undefined
   	const cacheWrite = usage.prompt_tokens_details?.cache_write_tokens ?? undefined
   	const reasoning = usage.completion_tokens_details?.reasoning_tokens ?? undefined
   	const nonCached = ProviderShared.subtractTokens(input, ProviderShared.sumTokens(cached, cacheWrite))
   	return new Usage({
   	inputTokens: input,
   	outputTokens: output,
   	nonCachedInputTokens: nonCached,
   	cacheReadInputTokens: cached,
   	cacheWriteInputTokens: cacheWrite,
   	reasoningTokens: reasoning,
   	totalTokens: ProviderShared.totalTokens(input, output, usage.total_tokens ?? undefined),
   	providerMetadata: { openai: usage },
   	})
   	}

   DeepSeek reports prompt_cache_hit_tokens / prompt_cache_miss_tokens at the top level of usage
   (per your report — I have no DeepSeek traffic to verify the wire shape myself), so neither key is
   matched. #36749 hits the identical wall with a gateway sending cache_creation_input_tokens.

   Both keys already survive decoding, because the usage struct carries a rest record:

   opencode/packages/ai/src/protocols/openai-chat.ts

   Lines 155 to 181 in 39be159

   	const OpenAIChatUsage = Schema.StructWithRest(
   	Schema.Struct({
   	prompt_tokens: optionalNull(Schema.Number),
   	completion_tokens: optionalNull(Schema.Number),
   	total_tokens: optionalNull(Schema.Number),
   	prompt_tokens_details: optionalNull(
   	Schema.StructWithRest(
   	Schema.Struct({
   	cached_tokens: optionalNull(Schema.Number),
   	cache_write_tokens: optionalNull(Schema.Number),
   	}),
   	[Schema.Record(Schema.String, Schema.Unknown)],
   	),
   	),
   	completion_tokens_details: optionalNull(
   	Schema.StructWithRest(
   	Schema.Struct({
   	reasoning_tokens: optionalNull(Schema.Number),
   	accepted_prediction_tokens: optionalNull(Schema.Number),
   	rejected_prediction_tokens: optionalNull(Schema.Number),
   	}),
   	[Schema.Record(Schema.String, Schema.Unknown)],
   	),
   	),
   	}),
   	[Schema.Record(Schema.String, Schema.Unknown)],
   	)

   So the fix is additive inside mapUsage — read the provider's own key names before falling back to
   the subtraction. No schema change.

   Worth flagging why nobody notices until the bill arrives: prompt_tokens is inclusive, and nonCached
   is derived as prompt_tokens - (cached + cacheWrite). With cacheWrite undefined the miss tokens stay
   inside nonCached and the totals still reconcile exactly, so cache.write: 0 is not accompanied by
   any other symptom. Your requested hit / (hit + miss) ratio is unrecoverable from the stored message
   for the same reason — providerMetadata is not persisted, so the raw counts are gone by then.
4. neriousy

   marked fix: cache write tokens always 0 for Anthropic models behind an OpenAI-compatible provider #36749 as a duplicate of this issue on Oct 1, 2026
5. thdxr commented on Oct 11, 2026

   

   thdxr

   on Oct 11, 2026

   Member

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   Thanks for the report! OpenCode 2.0 is now out and development is focused on V2, so we're closing issues filed against OpenCode 1. Please upgrade (opencode upgrade --major, details: https://anoma.ly/notes/opencode-2-0), and if this is still relevant on 2.0, reopen this issue or open a new one with your 2.0 version.

   — from 𝕺𝖕𝖊𝖓𝕮𝖔𝖉𝖊
6. thdxr

   closed this as not plannedon Oct 11, 2026